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  1. Last updated 5/2020 MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz Language: English | Size: 1.13 GB | Duration: 1h 15m Research paper development; research paper writing and development; learning to write a paper for anyone; any learner. What you'll learn Writing a research paper Requirements Google drive, google docs; Microsoft word, whatever is available, a computer Description In this course, we will be modeling how to write a research paper. From running head to cover page, the initial purpose of this course is intended to prepare anyone to learn how to write a paper. Through templates that will be given out in this course, we will give anyone (high school, undergraduate, or graduate) an effective way that should definitely earn you an A! Overview Section 1: Introduction to Writing a Research Paper: Example of a B Paper Lecture 1 Research Paper/Public Speaking compared Lecture 2 Lecture 3: A Literature Review Lecture 3 Mind Mapping Lecture 4 Mind Mapping 2 Lecture 5 Preparation Outline Lecture 6 Mind Map Research Topic Lecture 7 Template for Research Paper Lecture 8 Lecture 8: You must have an open mind Lecture 9 Template PDF high school students, undergraduate students, gradate students; anyone who wants to write research paper Homepage https://www.udemy.com/course/writing-a-research-paper-learning-to-do-your-own-research/ Download from UploadCloud https://www.uploadcloud.pro/85wde2t52anh/ontyu.Writing.A.Research.Paper.Learning.To.Do.Your.Own.Research..part1.rar.html https://www.uploadcloud.pro/n66iaynsxdt8/ontyu.Writing.A.Research.Paper.Learning.To.Do.Your.Own.Research..part2.rar.html Download ( Rapidgator ) https://rapidgator.net/file/0206cb77dbab9fe7f7a2a3c526b20021/ontyu.Writing.A.Research.Paper.Learning.To.Do.Your.Own.Research..part2.rar.html https://rapidgator.net/file/8241ff6fcfd64081c34b8231eec6ad82/ontyu.Writing.A.Research.Paper.Learning.To.Do.Your.Own.Research..part1.rar.html [b]Download (Uploadgig)[/b] https://uploadgig.com/file/download/26347057bBc5d358/ontyu.Writing.A.Research.Paper.Learning.To.Do.Your.Own.Research..part2.rar https://uploadgig.com/file/download/Ac692BCf572567af/ontyu.Writing.A.Research.Paper.Learning.To.Do.Your.Own.Research..part1.rar Download ( NitroFlare ) https://nitroflare.com/view/580F6F893DC48A7/ontyu.Writing.A.Research.Paper.Learning.To.Do.Your.Own.Research..part1.rar https://nitroflare.com/view/5C1A64CAD8CCB0A/ontyu.Writing.A.Research.Paper.Learning.To.Do.Your.Own.Research..part2.rar Links are Interchangeable - No Password - Single Extraction
  2. Last updated 10/2021 MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz Language: English | Size: 2.48 GB | Duration: 7h 1m Teach and learn Computer Networking the proper way using the Microsoft Networking Fundamentals (Exam 98-366) Curriculum What you'll learn Very Similar to my INE Course Learn how to teach Computer Networking using step-by step theory & project-based lectures (For Instructors) Teach Computer Networking using logical and systematic methods (For Instructors) Build and practice with your network as you learn (for students) Prepare for the MTA - Networking Fundamentals: Exam 98-366 using step-by-step learning methods (for students) Learn about LANs, Addressing, Media Types, Topologies, Switching & Networking Models Learn about WANs, Routing, Remote Access, and Security Learn about Networking Services: DNS and DHCP Requirements Basic Computer and IT Skills (For Students) CompTIA Network+ or CCNA at least is recommended (For Instructors) Experience in teaching Computer Networking or desire to teach this topic (For Instructors) Description ***** Very Similar to my INE Course *****When you learn or teach Computer Networking, you might wonder about how topics should be explained. Should theory concepts such as OSI and TCP/IP models be explained first? Then how students will fully understand and comprehend ideas related to these models such as MAC and IP addresses and how they work in networks? Should they try to imagine this in their minds? And if the addressing concepts were explained first, then how can students fully understand these concepts without seeing them in action before moving to other concepts? Here we see that some practice is needed along with the theory explanation of these concepts. And should the students practice with individual mini labs or with full network from the start that would terrify them with its looking? This course progresses through concepts and topics using step-by step theory & project-based logical and systematic methods which is the solution for these issues. Students should learn with a mixture of theory and practice that moves from one topic to another related one while their network or project grows little by little. So as an example for this step-by-step learning method, in the first lectures, you will learn about what is a computer network, and what are local area networks or LANs, since those are the most basic form of a network you will encounter in real world. After that we have to understand network addresses in order to assign them to devices in our network, and thus enable communication between those devices. But before that, we have to understand numbering systems, such as binary and hexadecimal, since network addresses such as IPv4, IPv6, and MAC are implemented using these numbering systems. Now as you have understood the concepts of network addressing, it is time to practice with them, and we will use Cisco packet Tracer for that purpose. Afterwards, you have to understand how to map between different types of addresses using ARP, or the Address Resolution Protocol, and why this mapping is needed. Also ICMP or the Internet Control Message Protocol will be explained to demonstrate how communication in computer networks works. And again will we practice both ARP and ICMP using Packet Tracer in order to understand the concepts, and start establishing our hands on expertise. The same logical order of topics or lectures will continue to the end of the course. We will use the the MTA: Networking fundamentals curriculum to learn about Computer Networking and build our network through this course.MTA or Microsoft Technology Associate is an entry-level certification that provides the fundamentals of a certain technology based on Microsoft products. The MTA: Networking Fundamentals (exam 98-366) is one of these certifications that will provide essential networking knowledge and skills to you. This certification can be your first step in networking and towards other advanced Microsoft certifications such as MCSA and MCSE. It can be considered as the Microsoft version of Network+ or Cisco ICND1/CCENT. This course will help you to prepare for this certification through building a network step by step, going from LAN, addressing, switching, topologies, media types, and networking models to WAN, routing, remote access, security, and network services. With each step, you will learn the theory and practical skills related to it.I hope that you will join me in this course and start your journey of leaning or teaching computer networking. Happy learning and inspirational teaching! Overview Section 1: Intoduction Lecture 1 Course Introduction & Overview Lecture 2 Introduction to Networking Section 2: LANs, Addressing, Media Types, Topologies, Switching & Networking Models Lecture 3 Understanding Local Area Networks (LANs) Lecture 4 Understanding Numbering Systems Lecture 5 Understanding Network Addressing Lecture 6 Introducing Packet Tracer & Working with Addressing Lecture 7 Understanding ARP & ICMP Lecture 8 Working with ARP & ICMP Lecture 9 Wired Network Media Lecture 10 Network Topologies Lecture 11 Token Ring a& FDDI Lecture 12 Understanding Ethernet Lecture 13 Working with Hubs Lecture 14 Working with Switches Lecture 15 Understanding Subnetting & Default Gateways Lecture 16 Working with Subnetting Lecture 17 Invalid IP Addresses Lecture 18 Configuring Default Gateways Lecture 19 Understanding Proxy ARP Lecture 20 Configuring Hosts with a Default Gateway Lecture 21 Disabling Proxy ARP Lecture 22 Understanding VLANs Lecture 23 Working with VLANs Lecture 24 Understanding OSI Lecture 25 Understanding TCP/IP Lecture 26 Working with FTP Lecture 27 Working with TCP & HTTP Lecture 28 Working with the NETSTAT Command Lecture 29 Understanding IPv6 Lecture 30 Working with IPv6 Lecture 31 Understanding Wireless Media Lecture 32 Configuring & Working with Wireless Devices Section 3: WANs, Routing, Remote Access, and Security Lecture 33 Understanding WANs Lecture 34 Understanding Routing Lecture 35 Configuring Static Routing Lecture 36 Working with Dynamic Routing - RIP Lecture 37 Working with Tracert & Pathping Commands Lecture 38 Security & Remote Access Lecture 39 Configuring Default Routes & Working with NAT Section 4: Networking Services: DNS and DHCP Lecture 40 Understanding DNS Lecture 41 Configuring & Working with DNS & the NSLOOKUP Command Lecture 42 Understanding DHCP Lecture 43 Configuring & Working with DHCP Lecture 44 Working with GNS3 & Wireshark Lecture 45 Other TCP/IP Commands Lecture 46 Networking Technology Advancements - SDN Section 5: Bonus Lecture: More courses - Lowest Price Lecture 47 Bonus Lecture: More courses - Lowest Price IT Instructors who want to teach Computer Networking using step-by step theory & project-based logical and systematic methods,Students who want to learn Computer Networking from scratch the proper way using systematic methods with logical order,Students who want to study the MTA - Networking Fundamentals (Exam 98-366) Curriculum Homepage https://www.udemy.com/course/mta-networking-fundamentals-teaching-and-learning/ Download from UploadCloud https://www.uploadcloud.pro/37ctmddk7395/jjmky.Mta..Networking.Fundamentals.Teaching.And.Learning.part2.rar.html https://www.uploadcloud.pro/xv4yc470xz41/jjmky.Mta..Networking.Fundamentals.Teaching.And.Learning.part3.rar.html https://www.uploadcloud.pro/yfxq0qos9mim/jjmky.Mta..Networking.Fundamentals.Teaching.And.Learning.part1.rar.html Download ( Rapidgator ) https://rapidgator.net/file/1ef3e87fcee63150e3948afd0060f3cb/jjmky.Mta..Networking.Fundamentals.Teaching.And.Learning.part3.rar.html https://rapidgator.net/file/21a46919bfeca4a7cb62d4fefa1ca52c/jjmky.Mta..Networking.Fundamentals.Teaching.And.Learning.part2.rar.html https://rapidgator.net/file/97cd03cb4c06b3e4d6a48f129239267f/jjmky.Mta..Networking.Fundamentals.Teaching.And.Learning.part1.rar.html [b]Download (Uploadgig)[/b] https://uploadgig.com/file/download/27F4e738add8c810/jjmky.Mta..Networking.Fundamentals.Teaching.And.Learning.part2.rar https://uploadgig.com/file/download/a7D09a8df8859349/jjmky.Mta..Networking.Fundamentals.Teaching.And.Learning.part3.rar https://uploadgig.com/file/download/aba17e22daC8c1F8/jjmky.Mta..Networking.Fundamentals.Teaching.And.Learning.part1.rar Download ( NitroFlare ) https://nitroflare.com/view/4865CF766DE718A/jjmky.Mta..Networking.Fundamentals.Teaching.And.Learning.part2.rar https://nitroflare.com/view/730B3D6AD969E8A/jjmky.Mta..Networking.Fundamentals.Teaching.And.Learning.part3.rar https://nitroflare.com/view/D3FA4139BD78927/jjmky.Mta..Networking.Fundamentals.Teaching.And.Learning.part1.rar Links are Interchangeable - No Password - Single Extraction
  3. Released 08/2022 MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Skill Level: Intermediate | Genre: eLearning | Language: English + srt | Duration: 1h 20m | Size: 318.1 MB Ever wondered what's really going on underneath a machine learning algorithm? The answer is linear algebra. Without it, machine learning can't exist. Linear algebra is a prerequisite for understanding and creating nearly all machine learning algorithms, especially those that prop up neural networks, natural language processing tools, and deep learning models. Join instructor Terezija Semenski for an in-depth exploration of the core concepts of linear algebra alongside the techniques needed to design and implement a successful machine learning algorithm. Discover the basics of vector arithmetic, vector norms, matrix properties, advanced operations, matrix transformation, and algorithms like Google PageRank. By the end of this course, you'll be ready to take the principles of linear algebra and apply them to your next big machine learning project. Homepage https://www.linkedin.com/learning/machine-learning-foundations-linear-algebra Download from UploadCloud https://www.uploadcloud.pro/m6ncvm4gxx6z/ijado.Machine.Learning.Foundations.Linear.Algebra.rar.html Download ( Rapidgator ) https://rapidgator.net/file/ef9ab4f525e32689e0e8e3aba08e3c1b/ijado.Machine.Learning.Foundations.Linear.Algebra.rar.html [b]Download (Uploadgig)[/b] https://uploadgig.com/file/download/c8F9c52e32A0F3cc/ijado.Machine.Learning.Foundations.Linear.Algebra.rar Download ( NitroFlare ) https://nitroflare.com/view/37D84FF4E3251F8/ijado.Machine.Learning.Foundations.Linear.Algebra.rar Links are Interchangeable - No Password - Single Extraction
  4. Released 08/2022 MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Skill Level: Intermediate | Genre: eLearning | Language: English + srt | Duration: 1h 20m | Size: 318.1 MB Ever wondered what's really going on underneath a machine learning algorithm? The answer is linear algebra. Without it, machine learning can't exist. Linear algebra is a prerequisite for understanding and creating nearly all machine learning algorithms, especially those that prop up neural networks, natural language processing tools, and deep learning models. Join instructor Terezija Semenski for an in-depth exploration of the core concepts of linear algebra alongside the techniques needed to design and implement a successful machine learning algorithm. Discover the basics of vector arithmetic, vector norms, matrix properties, advanced operations, matrix transformation, and algorithms like Google PageRank. By the end of this course, you'll be ready to take the principles of linear algebra and apply them to your next big machine learning project. Homepage https://www.linkedin.com/learning/machine-learning-foundations-linear-algebra Download from UploadCloud https://www.uploadcloud.pro/m6ncvm4gxx6z/ijado.Machine.Learning.Foundations.Linear.Algebra.rar.html Download ( Rapidgator ) https://rapidgator.net/file/ef9ab4f525e32689e0e8e3aba08e3c1b/ijado.Machine.Learning.Foundations.Linear.Algebra.rar.html [b]Download (Uploadgig)[/b] https://uploadgig.com/file/download/c8F9c52e32A0F3cc/ijado.Machine.Learning.Foundations.Linear.Algebra.rar Download ( NitroFlare ) https://nitroflare.com/view/37D84FF4E3251F8/ijado.Machine.Learning.Foundations.Linear.Algebra.rar Links are Interchangeable - No Password - Single Extraction
  5. Published 8/2022 MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz Language: English | Size: 652.56 MB | Duration: 0h 35m How to increase engagement and efficiency of your online courses What you'll learn Understand what learning objects are and how they impact teaching and learning in online courses What are the types of learning objects How to apply the most different types of objects in your online courses to improve engagement and efficiency List of tools for you to create the learning objects presented in the course Requirements None! Description Answer the following questions:Do you create online courses with only videos, texts, PDFs and multiple choice exercises?Would you like to exercise your student's brain more with more playful activities?Do you want to increase the efficiency and engagement of your course, and the teaching-learning process?Well, you need to better understand what learning objects are or, at least, how to diversify correctly within your courses! Discover various learning objects to use in your courses and increase student engagement!WHAT ARE EDUCATIONAL OBJECTS?In essence, every resource used to teach online can be considered a learning object - from the most basic such as text and video, to more complex interactive resources.This course aims to show you the possibilities you have within the digital environment, to get away from the sameness and the predictable. You are online, the possibilities are many.Learn to engage your students more by creating courses with more interactive and interesting content.AT THE END OF THIS COURSE, YOU WILL LEARN:Understand what learning objects are and how they impact teaching and learning in online coursesWhat are the types of learning objectsHow to apply the most different types of objects in your online courses to improve engagement and efficiencyList of tools for you to create the educational objects presented in the courseWHO IS YOUR INSTRUCTOR?My name is Ivan Chagas, I have been an instructor here since 2016 and I have over 11,000 students, in courses in Portuguese, English and Spanish. I have been working with educational content for 10 years, organizing events, I was once an educational manager at one of the largest innovation schools in Brazil. Today I work full-time as an instructional designer and content creator, owner of my own agency. Overview Section 1: Understand what learning objects are Lecture 1 Course opening! Lecture 2 WHAT ARE LEARNING OBJECTS - And why do they matter Lecture 3 THE CATEGORIES OF LEARNING OBJECTS Lecture 4 The 3 categories of learning objects Lecture 5 HOW TO PAIR THE OBJECT WITH THE LESSON'S OBJECTIVES Section 2: The 3 types of educational objects: knowing each one Lecture 6 Exposition objects: teaching and learning Lecture 7 Active objects: learning by doing Lecture 8 Task objects: teaching and verifying Section 3: Completing the course: learning points Lecture 9 HOW DO I CREATE A Learning Object? Where can I use it? Lecture 10 List of tools for creating educational objects Instructional designers who want to revamp their arsenal of resources to improve their courses,Training and development professionals who want to understand and improve the possibilities of online courses,Anyone who works in online education and is tired of only creating courses with videos and multiple choice exercises Homepage https://www.udemy.com/course/learning-objects/ Download from UploadCloud https://www.uploadcloud.pro/1r16fub17p0h/hyjnm.Learning.Objects.For.Online.Courses.rar.html Download ( Rapidgator ) https://rapidgator.net/file/23865fb120ddc6857849a1d63d2098fa/hyjnm.Learning.Objects.For.Online.Courses.rar.html [b]Download (Uploadgig)[/b] https://uploadgig.com/file/download/912d59d5BB606d48/hyjnm.Learning.Objects.For.Online.Courses.rar Download ( NitroFlare ) https://nitroflare.com/view/76407208131D96D/hyjnm.Learning.Objects.For.Online.Courses.rar Links are Interchangeable - No Password - Single Extraction
  6. Last updated 3/2021 MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz Language: English | Size: 639.02 MB | Duration: 1h 53m Get to know Kubernetes and how to get started in the world of DevOps! What you'll learn Kubernetes history - where it came from Kubernetes Business Benefits Kubernetes Architecture - Masters, Nodes, Pods, Services & Deployments Understand the desired state and declarative model Installing Kubernetes - Minikube, GCP, AWS Working with Pods. Deploying your first pod Kubernetes Services Kubernetes Ingress and Egress Deploy a Service on Kubernetes Salary and Demand for DevOps Professionals (Kubernetes) Requirements Access to Cloud Services or local Linux machines Internet Access Multiple Monitors to avoid screen flipping Description Did You Know? Kubernetes DevOps engineers make a range in the United States of $140,000 to $265,000 annually. Kubernetes is one of the hottest skills in 2020. - GlassdoorThis Kubernetes Fundamentals course is aimed at providing you with the fundamental knowledge of the Kubernetes or K8s architecture along with hands-on practical labs to strengthen your knowledge of the Kubernetes core concepts.Kubernetes is an open-source system for automating deployment, scaling, and management of containerized applications. It was originally designed by Google and is now maintained by the Cloud Native Computing Foundation.Kubernetes is at the cutting-edge of application deployment. The best way to kick-start your DevOps career is by learning how to effectively deploy Kubernetes.The following topics are covered.· Kubernetes history - where it came from· Kubernetes - Business Benefits· Kubernetes Architecture - Masters, Nodes, Pods, Services & Deployments· Understand the desired state and declarative model· Installing Kubernetes on Minikube, GCP, AWS· Working with Pods. Deploying your first pod.· Kubernetes Services· Kubernetes Ingress and Egress· Kubernetes deployments. Creating your first deployment· Career Demand and Salaries. Kubernetes CertificationsWhat can you expect from the Kubernetes Fundamentals Course?· Full downloadable content· Kubernetes Demos· Whiteboard Discussions· Practice Questions· Exercises to follow alongWho would be the target audience?This course is for absolute Kubernetes beginners.This course is a beginners course and meant to be a 101 course. This course is the prerequirement for the TechCommanders Kubernetes Engine Course and the Certified Kubernetes Administrator (CKA) exam prep course. Overview Section 1: Module 1 - Course Introduction Lecture 1 Introduction Lecture 2 Course PreReqs Section 2: Module 2 - Basics of Kubernetes Lecture 3 Module 2 - Basics of Kubernetes Lecture 4 What is Kubernetes Lecture 5 Business Value of Kubernetes Lecture 6 What is a Container? Lecture 7 What is Docker? Lecture 8 Kubernetes History Lecture 9 Kubernetes Terminology Lecture 10 Kubernetes Components Lecture 11 Whiteboard Discussion - Kubernetes Overview Section 3: Module 3- Kubernetes Design and Architecture Lecture 12 Module 3- Kubernetes Design and Architecture Lecture 13 Kubernetes Design Fundamentals Lecture 14 Whiteboard Discussion - Kubernetes Architecture Lecture 15 Deployment - Nodes, Pods and Clusters Lecture 16 Etcd Lecture 17 kubectl Lecture 18 Demo - kubectl Lecture 19 Demo - CLI Commands Lecture 20 Demo - CLI Commands 2 Section 4: Module 4 - Deployments Lecture 21 Module 4 - Deployments Lecture 22 Options for Deploying Kubernetes Lecture 23 Deploying a Containerized Application Lecture 24 Minikube Lecture 25 Demo - Minikube Lecture 26 Demo - Kubernetes Cluster Lecture 27 Demo - Kubernetes Services Section 5: Module 5- Course Closeout Lecture 28 Module 5- Course Closeout Lecture 29 Course Review Lecture 30 Kubernetes Certifications Lecture 31 Additional Resources Lecture 32 DevOps Roles and Salary Demand Lecture 33 Course Closeout This course is for absolute Kubernetes beginners,No knowledge about Kubernetes needed Homepage https://www.udemy.com/course/learning-kubernetes-from-scratch/ Download ( Rapidgator ) https://rapidgator.net/file/a196233e489c39eb3474ab6de0ffa570/cuguy.Learning.Kubernetes.From.Scratch.rar.html [b]Download (Uploadgig)[/b] https://uploadgig.com/file/download/cabDE4122d5c2195/cuguy.Learning.Kubernetes.From.Scratch.rar Download ( NitroFlare ) https://nitroflare.com/view/EECDCEE55ECDE0F/cuguy.Learning.Kubernetes.From.Scratch.rar Links are Interchangeable - No Password - Single Extraction
  7. Last updated 1/2019 MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz Language: English | Size: 1.73 GB | Duration: 8h 31m Jump into a field with more demand than supply. Apps driven by machine learning are the future of mobile app development What you'll learn Learn to code in Python and Java Learn to use PyCharm and Android Studio Learn to use TensorFlow to build, train, and test machine learning models Build apps Understand and expand on machine learning concepts for your own projects Get tools to work in the future of the world around us as artificial intelligence becomes more prevalent in everything we do Requirements No prior experience necessary We will take you through the steps of downloading and installing Android Studio, PyCharm, and Python Description Python, Java, PyCharm, Android Studio and MNIST. Learn to code and build apps! Use machine learning models in hands-on projects. A wildly successful Kickstarter funded this courseExplore machine learning concepts. Learn how to use TensorFlow 1.4.1 to build, train, and test machine learning models. We explore Python 3.6.2 and Java 8 languages, and how to use PyCharm 2017.2.3 and Android Studio 3 to build apps. A machine learning framework for everyoneIf you want to build sophisticated and intelligent mobile apps or simply want to know more about how machine learning works in a mobile environment, this course is for you.Be one of the firstThere are next to no courses on big platforms that focus on mobile machine learning in particular. All of them focus specifically on machine learning for a desktop or laptop environment.We provide clear, concise explanations at each step along the way so that viewers can not only replicate, but also understand and expand upon what I teach. Other courses don't do a great job of explaining exactly what is going on at each step in the process and why we choose to build models the way we do. No prior knowledge is requiredWe will teach you all you need to know about the languages, software and technologies we use. If you have lots of experience building machine learning apps, you may find this course a little slow because it's designed for beginners.Jump into a field that has more demand than supplyMachine learning changes everything. It's bringing us self-driving cars, facial recognition and artificial intelligence. And the best part is: anyone can create such innovations."This course is GREAT! This is what I want!" -- Rated 5 Stars by Mammoth Interactive StudentsEnroll Now While On Sale Overview Section 1: Update! Resources Lecture 1 Resources Section 2: Intro to Android Studio Lecture 2 Intro to Android and Topics List Lecture 3 Downloading and Installing Android Studio Lecture 4 Exploring Interface Lecture 5 Setting up Emulator and Running Project Section 3: Intro to Java Lecture 6 Java Language Basics Lecture 7 Variable Types Lecture 8 Operations on Variables Lecture 9 Arrays and Lists Lecture 10 Array and List Operations Lecture 11 If and Switch Statements Lecture 12 While Loops Lecture 13 For Loops Lecture 14 Functions Intro Lecture 15 Parameters and Return Values Lecture 16 Classes and Objects Intro Lecture 17 Superclass and Subclasses Lecture 18 Static Variables and Axis Modifiers Section 4: Intro to App Development Lecture 19 Intro to Android App Development Lecture 20 Building Basic User Interface Lecture 21 Connecting UI to Backend Lecture 22 Implementing Backend and Tidying UI Section 5: Intro to ML Concepts Lecture 23 ML Concepts Intro Lecture 24 Intro to PyCharm and Topics List Lecture 25 Installing PyCharm and Python Lecture 26 Exploring PyCharm Lecture 27 (Files) Source Code Section 6: Python Language Basics Lecture 28 Intro to Variables Lecture 29 Variables Operations and Conversions Lecture 30 Collection Types Lecture 31 Collections Operations Lecture 32 Control Flow: If Statements Lecture 33 While and For Loops Lecture 34 Functions Lecture 35 Classes and Objects Lecture 36 (Files) Source Code Section 7: Intro to TensorFlow Lecture 37 TensorFlow Intro Lecture 38 Topics List Lecture 39 Installing TensorFlow Lecture 40 FAQ: Help with TensorFlow Installation Lecture 41 Importing TensorFlow to PyCharm Lecture 42 Constant Nodes and Sessions Lecture 43 Variable Nodes Lecture 44 Placeholder Nodes Lecture 45 Operation Nodes Lecture 46 Loss, Optimizers, and Training Lecture 47 Building a Linear Regression Model Lecture 48 (Files) Source Code Section 8: Simple MNIST Lecture 49 Simple MNIST Intro and Demo Lecture 50 Topics List and Intro to MNIST Data Lecture 51 Building Computational Graph Lecture 52 Training and Testing the Model Lecture 53 Save & Freeze Graph for Android Import Lecture 54 Setting up Android Studio Project Lecture 55 Building User Interface Lecture 56 Loading Digit Images Lecture 57 Formatting Image Data Lecture 58 Making Prediction Using Model Lecture 59 Displaying Results and Summary Lecture 60 (Files) Source Code Lecture 61 Please rate this course Lecture 62 Bonus Lecture: Newsletter Anyone who wants to use machine learning in a mobile environment Homepage https://www.udemy.com/course/mobilemachinelearning/ Download from UploadCloud https://www.uploadcloud.pro/3tym98pomf25/bvplc.HandsOn.Machine.Learning.Learn.Tensorflow.Python..Java.part1.rar.html https://www.uploadcloud.pro/rvarpi4gq0qx/bvplc.HandsOn.Machine.Learning.Learn.Tensorflow.Python..Java.part2.rar.html Download ( Rapidgator ) https://rapidgator.net/file/293db712b70243d14024145c4a2bc970/bvplc.HandsOn.Machine.Learning.Learn.Tensorflow.Python..Java.part2.rar.html https://rapidgator.net/file/bfd106718d84498b13852493f5bae246/bvplc.HandsOn.Machine.Learning.Learn.Tensorflow.Python..Java.part1.rar.html [b]Download (Uploadgig)[/b] https://uploadgig.com/file/download/13b033A7f29525bD/bvplc.HandsOn.Machine.Learning.Learn.Tensorflow.Python..Java.part2.rar https://uploadgig.com/file/download/a4000Fc95bF443dd/bvplc.HandsOn.Machine.Learning.Learn.Tensorflow.Python..Java.part1.rar Download ( NitroFlare ) https://nitroflare.com/view/40372BB09B1A7F9/bvplc.HandsOn.Machine.Learning.Learn.Tensorflow.Python..Java.part2.rar https://nitroflare.com/view/74E38D61260D032/bvplc.HandsOn.Machine.Learning.Learn.Tensorflow.Python..Java.part1.rar Links are Interchangeable - No Password - Single Extraction
  8. Last Updated 08/2022 MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Genre: eLearning | Language: English + srt | Duration: 56 lectures (1h 59m) | Size: 1.64 GB Accelerated learning skills for a competitive advantage in your career and life What you'll learn How to learn effectively Learn faster. Retain knowledge better. Stop procrastination. Make instant progress on developing your skills. The highest form of self-confidence is believing in your ability to learn. Learning isn't a way of reaching one's potential but rather a way of developing it. Want to move up? Then, you have to be a perpetual learner. Effective Learning Techniques and Strategies Learn How to learn How to use the Feynman technique How to synthesize key lessons taught by experience The more we know, the more information (hooks) we have to connect new information to, the easier we can form long-term memories. MEMORIZE AND RETAIN MORE KNOWLEDGE Get more knowledge in your head with effective tips START ENJOYING YOUR STUDYING Find your own education style that fits you perfectly FIGHT YOUR PROCRASTINATION Strike a balance between perfectionism and procrastination Problem Solving Strategies and Systems to tackle any problem or obstacles you may encounter. Understand the importance of Numeracy. How the Brain Works in Learning. Effective Learning Strategies to Ultra Boost Learning Speeds. Tips to Improve Memorization and Retainability. How to Take Powerful Notes. Breaking The Curse of Procrastination. How to do Research. Problem Solving Methods to Tackle Any Problem. Lifetime Techniques for Mastering Any Skill. Learning how to learn is the ultimate key to improving your confidence, your career prospects, and your personal life. BONUS: How to Take Advantage of Sleep to Process Information Faster. Requirements No experience needed. Description The path to success is the continuous pursuit of knowledge. Learning how to learn is the ultimate key to improving your confidence, your career prospects, and your personal life. "Formal education will make you a living; self-education will make you a fortune." - Jim Rohn The highest form of self-confidence is believing in your ability to learn. Learning new skills can be a great way to improve your life and career. Learning isn't a way of reaching one's potential but rather a way of developing it. Want to move up? Then, you have to be a perpetual learner. It's one thing to know how to learn new things, but it's another thing entirely to be good at it. Learning how to learn will help you pick up new skills more quickly and effectively. Learning is a treasure that will follow its owner everywhere. - Chinese proverb Learning to learn is the ability to pursue and persist in learning, to organize one's own learning, including through effective management of time and information, both individually and in groups. Benefits of Learning How to Learn You'll learn better You'll remember more You'll find ways to apply your knowledge You'll find new ways to improve your career and your life with new knowledge You'll be able to share your knowledge with others You'll be a better person You'll have more self-respect You'll be respected by others You'll influence others to be better You'll be more confident You'll discover hidden talents You'll find a use for your skills when you least expect it You'll have fun while learning skills You'll become more interesting You'll learn faster You'll become more open-minded You'll build a habit of failure (yes, that's a good thing) You'll raise your energy You'll boost your confidence You'll have more ways to earn money The first half of my life I went to school, the second half of my life I got an education. How To Accelerate Your Learning Capabilities Effective learning techniques to stay miles ahead of your competition What you'll learn ● How the Brain Works in Learning. ● Effective Learning Strategies to Ultra Boost Learning Speeds. ● Tips to Improve Memorization and Retainability. ● Breaking The Curse of Procrastination. ● How to Take Powerful Notes. ● How to do Research. ● Problem Solving Methods to Tackle Any Problem. ● Lifetime Techniques for Mastering Any Skill. ● BONUS: How to Take Advantage of Sleep to Process Information Faster. In times of change, learners inherit the earth, while the learned find themselves beautifully equipped to deal with a world that no longer exists. Your best ROI is not a return on your investment, but a return on your information. Learning how to learn is life's most important skill. Why does learning matter? These little information edges turn out to be the difference between half-measure wannabes and a literal winner. One skill you want to master in this day and age we live in, if you want to have an extraordinary life, is the ability to learn rapidly. Learning how to learn is the most powerful tool you can ever grasp and your life will be enriched beyond measure. The global economy has shifted from a material-based to a knowledge-based model. Whereas material assets such as gold mines, wheat farms, and oil wells were historically the primary sources of riches, knowledge is now the primary source of prosperity. The best thing a person can do is help another person learn more. Banking on living a "traditional" life: going to college, getting a job for a big firm, working hard, and climbing the corporate ladder, might not make sense. Instead, young people today should learn as much as possible and develop a flexible set of skills, so they can re-adapt themselves to whatever the future holds. The path to success is the continuous pursuit of knowledge. We call this pursuit learning. Learning how to learn is the most important skill we can develop in the twenty first century. Almost anything in life can be learned faster. Most people learn passively. They wait for insights to come to them. But you can speed things up by actively searching for useful ideas. One strategy is to ask top people you meet what they do. Make their best practices your baseline. Another is to use this course to accelerate the process. The ability to take responsibility for your growth - self-directed learning is a superpower in the age of knowledge abundance. Let's get to it! Inevitably, some people will be on the losing end of change even as the robots make society as a whole better off. One lesson from the freewheeling globalization of the 1990s and 2000s is that the growth in trade that was overwhelmingly beneficial triggered a political backlash, because the losers felt left behind. That is one more reason why firms and governments would do well to recognize the value of retraining and lifelong learning. As jobs change, workers should be helped to acquire new skills. An expert is someone who, over many years, manages to remain confident enough to keep trying and humble enough to keep learning. Learning is the only thing the mind never exhausts, never fears, and never regrets - Leonardo Da Vinci The path to success is the continuous pursuit of knowledge. Success is the product of accumulative advantage. This course will cover accelerated learning and the retention of knowledge. The famous futurist Alvin Toffler once said, "The illiterate of the future are not those who can't read or write but those who cannot learn, unlearn, and relearn." What got you here won't get you where you want to go. "Knowledge is exploding, so you need to commit yourself to a plan for lifelong learning." - Don Tapscott "The most important skill for getting rich is becoming a perpetual learner. You have to know how to learn anything you want to learn. - Naval Lifelong learners are not afraid to unlearn to relearn. Beware of false knowledge. What you know could be holding you back. Learning to learn is a valuable skill in the modern world. Their long term goal is personal satisfaction. The bigger goal of learning can help you lead a meaningful and fulfilling life. Over the long term, lifelong learners learn more from unstructured learning than from formal education. School gets you started; self-learning keeps you going. What you will learn How the brain works in learning Focused and Diffused Thinking How the brain uses two very different learning modes and how it encapsulates ("chunks") information. The Feynman Technique Dealing with procrastination test-taking tips Seinfeld's Productivity Secret Pomodoro Technique Creativity Memorization techniques Create a Personal Knowledge Management System Mind Mapping How to take notes How to Read for Knowledge acquisition How to create a Personal Knowledge Management (PKM) system (what is sometimes called a second brain) How to do Research How to take advantage of sleep and your unconscious mind, priming yourself to assimilate information and solve problems more efficiently. This course gives you easy access to the invaluable learning techniques used by experts in art, music, literature, math, science, sports, and many other disciplines. We'll learn about how the brain uses two very different learning modes and how it encapsulates ("chunks") information. We'll also cover illusions of learning, memory techniques, dealing with procrastination, and best practices shown by research to be most effective in helping you master tough subjects. Using these approaches, no matter what your skill levels in topics you would like to master, you can change your thinking and change your life. If you're already an expert, this peep under the mental hood will give you ideas for turbocharging successful learning, including counter-intuitive test-taking tips and insights that will help you make the best use of your time on homework and problem sets. If you're struggling, you'll see a structured treasure trove of practical techniques that walk you through what you need to do to get on track. If you've ever wanted to become better at anything, this course will help serve as your guide. Break Through Obstacles to Learning and Discover Your Hidden Potential This course reveals how we can overcome stereotypes and preconceived ideas about what is possible for us to learn and become. The famous futurist Alvin Toffler once said, "The illiterate of the future are not those who can't read or write but those who cannot learn, unlearn, and relearn." At a time when we are constantly being asked to retrain and reinvent ourselves to adapt to new technologies and changing industries, this course shows us how we can uncover and develop talents we didn't realize we had-no matter what our age or background. Drawing on the latest neuroscientific insights, this course shepherds us past simplistic ideas of "aptitude" and "ability," which provide only a snapshot of who we are now-with little consideration about how we can change. Even seemingly "bad" traits, such as a poor memory, come with hidden advantages-like increased creativity. We can turn perceived weaknesses, such as impostor syndrome and advancing age, into strengths. People may feel like they're at a disadvantage if they pursue a new field later in life; yet those who change careers can be fertile cross-pollinators: They bring valuable insights from one discipline to another. John Cousins teaches us strategies for learning that are backed by neuroscience so that we can realize the joy and benefits of a learning lifestyle. Become a Learning Ninja takes us deep inside the world of how people change and grow. Our biggest stumbling blocks can be our own preconceptions, but with the right mental insights, we can tap into hidden potential and create new opportunities. How to learn effectively Learn faster. Retain knowledge better. Stop procrastination. Make instant progress on developing your skills. Who this course is for If you feel you're capable of more and need to start functioning in your full capacity If your learning is ineffective and you need to start to acquire knowledge better If you want to become better at anything and need a firm framework to guide you What You will learn MEMORIZE AND RETAIN MORE KNOWLEDGE Get more knowledge in your head with effective tips START ENJOYING YOUR STUDYING Find your own education style that fits you perfectly FIGHT YOUR PROCRASTINATION Strike a balance between perfectionism and procrastination Start a course on effective learning, and get smarter! Learn how to grasp new information and build a growth mindset. Discover hacks to fight procrastination, stay focused, and use your mind effectively. Course syllabus is based on concepts and ideas from the latest niche researches, top university courses, specialized books and expert articles. Who this course is for People who want to understand how to learn quickly and effectively. In the twenty first century the greatest skill is to know how to learn, unlearn and relearn. Learning how to learn is life's most important skill. The ability to take responsibility for your growth - self-directed learning is a superpower in the age of knowledge abundance. If you feel you're capable of more and need to start functioning in your full capacity If your learning is ineffective and you need to start to acquire knowledge better If you want to become better at anything and need a firm framework to guide you Your best ROI is not a return on your investment, but a return on your information. In times of change, learners inherit the earth, while the learned find themselves beautifully equipped to deal with a world that no longer exists. Homepage https://www.udemy.com/course/become-a-learning-ninja/ Download from UploadCloud https://www.uploadcloud.pro/2i8ycqprk1sx/zisoe.Become.a.Learning.Ninja.part1.rar.html https://www.uploadcloud.pro/cfyw0d64kcdb/zisoe.Become.a.Learning.Ninja.part2.rar.html Download ( Rapidgator ) https://rapidgator.net/file/0c6714e05c466ad092f71f6a2b576d00/zisoe.Become.a.Learning.Ninja.part2.rar.html https://rapidgator.net/file/b1f98bc9022d16f6bfe34722baba7655/zisoe.Become.a.Learning.Ninja.part1.rar.html [b]Download (Uploadgig)[/b] https://uploadgig.com/file/download/063476883b31d9d0/zisoe.Become.a.Learning.Ninja.part1.rar https://uploadgig.com/file/download/625c0879c2cea314/zisoe.Become.a.Learning.Ninja.part2.rar Download ( NitroFlare ) https://nitroflare.com/view/8C1972B460AC8DD/zisoe.Become.a.Learning.Ninja.part2.rar https://nitroflare.com/view/A0FE242D114BF0D/zisoe.Become.a.Learning.Ninja.part1.rar Links are Interchangeable - No Password - Single Extraction
  9. Last updated 8/2019 MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz Language: English | Size: 58.93 GB | Duration: 110h 6m Learn how successful people trade and invest! Dominate the world of Finance with Python and Machine Learning! What you'll learn How Stocks Are Created Understand Stock Market Fundamentals Read Algorithms, Strategies, and Different Kinds of Graphs Get your hands dirty with real world coding examples and learn to code in Python. Handle Inputs and Outputs, Imports, Errors, and use Lists, Loops, Sets, and Dictionaries in Python. And More! Requirements These tutorials were recorded on a Mac computer using Python 3.5. To follow along with these tutorials, you will need to install Python. Python is compatible with Mac and PC. Description We at Mammoth Interactive value input from students like you. Feel free to leave us your feedback. Learn complete Python trading and coding from scratch. Become an expert in data analytics and real-world financial analysis. We are proud to present one of the most interesting and complete courses we've created so far. No experience is required.Through Mammoth Interactive's self-paced online learning, finance theory is not overwhelming like it would be in a regular university.Wall Street Coder will guide you through everything you need to know to use Python for Finance and Algorithmic Trading. We'll start off by learning the fundamentals of Python and proceed to learn about machine learning and Quantopian.The lessons are supplemented with handful of helpful source files you can refer back to at any time - forever! PLUS: Offline viewing on the Udemy iOS app. Lifetime access to all content.If you have always wanted to learn to code, this is your place to start. In this course, you will learn how to code in the Python 3.5 programming language. Whether you have or have not coded before, you can learn how to use Python. Python is a popular programming language that is useful to know because of its versatility. Python is easy to understand and can be used for many different environments.Cross-platform apps and 3D environments are often made in Python.This course does not assume any level of experience and is therefore perfect for beginners! We will cover basic programming concepts for people who have never programmed before. This course covers key topics in Python and coding in general, including variables, loops, and classes. Moreover, you will learn how to handle input, output, and errors.To learn how to use Python, we will create our own functioning Blackjack game! In this game, you will receive cards, submit bets, and keep track of your score. By the end of this course, you will be able to use the coding knowledge you gained to make your own apps and environments in Python.Also now included in these bundles are our extra courses. If you want to learn to use other programs such as Camtasia or Sketch, you get more content than what you paid for this way!We really hope you decide to purchase this course and take your knowledge to the next level. Let's get started.Enroll now to join the Mammoth community! Overview Section 1: Python Language Basics Lecture 1 Intro to Python Lecture 2 Summary of Python Section 2: Variables Lecture 3 Variables Lecture 4 Variables Demo Lecture 5 Variable Operators Lecture 6 Variable Operators Demo Lecture 7 Source Files - Variables Section 3: Collections Lecture 8 Lists Lecture 9 Tuples Lecture 10 Dictionaries Lecture 11 Matrices Lecture 12 Source Files - Collections Section 4: Control Flow Lecture 13 If Statements Lecture 14 While Loops Lecture 15 For Loops Lecture 16 Control Flow Statements Lecture 17 Source Files - Control Flow Section 5: Functions Lecture 18 Function Lecture 19 Parameters and Return Values Lecture 20 Source Files - Functions Section 6: Classes and Objects Lecture 21 Classes and Objects Lecture 22 Using Objects Lecture 23 Static Class Members Lecture 24 Inheritance Lecture 25 Source Files - Classes and Objects Section 7: Numpy Tutorials Lecture 26 Numpy Course Intro Lecture 27 Installing Numpy Lecture 28 Numpy Data Types Lecture 29 Numpy Arrays Lecture 30 Numpy Array Functions Lecture 31 Creating Numpy Matrices Lecture 32 Numpy Matrix Functions Lecture 33 Numpy Course Summary Lecture 34 Source Files - Numpy Tutorials Section 8: Pandas Tutorials Lecture 35 Pandas 101 Course Lecture 36 Installing Pandas Lecture 37 Pandas Data Types Lecture 38 Pandas Data Types Demo Lecture 39 Creating Series Demo Lecture 40 Creating Series Demo (Cont'd) Lecture 41 Series Function Lecture 42 Series Functions Demo Part 1 Lecture 43 Series Functions Demo Part 2 Lecture 44 Creating Dataframes Lecture 45 Creating Dataframe Demo Lecture 46 Dataframers Functions Lecture 47 Dataframes Functions Demo (Part 1) Lecture 48 Dataframes Functions Demo (Part 2) Lecture 49 Pandas 101 Course Summary Lecture 50 Source Files - Pandas Tutorials Section 9: PyPlot Tutorials Lecture 51 Pyplot Course Intro Lecture 52 Installing Pyplot Lecture 53 Plotting with PyPlot Lecture 54 Plotting with PyPlot Demo Lecture 55 Customizing Graphs Lecture 56 Customizind Graph Demo Lecture 57 Different Graph Types Lecture 58 PyPlot Course summary Lecture 59 Intro to Pyplot Slides Lecture 60 Source Files - PyPlot Tutorials Section 10: Basics of Programming Lecture 61 Introduction to Python Lecture 62 Variables Lecture 63 Functions Lecture 64 if Statements Section 11: Lists Lecture 65 Introduction to Lists Section 12: Loops Lecture 66 Introduction to and Examples of using Loops Lecture 67 Getting familiar with while Loops Lecture 68 Breaking and Continuing in Loops Lecture 69 Making Shapes with Loops Lecture 70 Nested Loops and Printing a Tic-Tac-Toe field Section 13: Sets and Dictionaries Lecture 71 Understanding Sets and Dictionaries Lecture 72 An Example for an Invetory List Section 14: Input and Output Lecture 73 Introduction and Implementation of Input and Output Lecture 74 Introduction to and Integrating File Input and Output Lecture 75 An example for a Tic-Tac-Toe Game Lecture 76 An example of a Tic-Tac-Toe Game (Cont'd) Lecture 77 An Example writing Participant data to File Lecture 78 An Example Reading Participant Data from File Lecture 79 Doing some simple statistics with Participant data from File Section 15: Classes Lecture 80 A First Look at Classes Lecture 81 Inheritance and Classes Lecture 82 An Example of Classes using Pets Lecture 83 An Example of Classes using Pets - Dogs Lecture 84 An examples of Classes using Pets - Cats Lecture 85 Taking The Pets Example further and adding humans Section 16: Importing Lecture 86 Introduction to Importing and the Random Library Lecture 87 Another way of importing and using lists with random Lecture 88 Using the Time Library Lecture 89 Introduction to The Math Library Lecture 90 Creating a User guessing Game with Random Lecture 91 Making the Computer guess a random number Section 17: Project Blackjack Game Lecture 92 BlackJack Game Part 1 - Creating and Shuffling a Deck Lecture 93 Blackjack Game Part 2 - Creating the player class Lecture 94 Blackjack Game Part 3 - Expanding the Player Class Lecture 95 Blackjack Game Part 4 - Implementing a bet and win Lecture 96 Blackjack Game Part 5 - Implementing the player moves Lecture 97 Blackjack Game Part 6 - Running the Game (Final) Section 18: Error Handling Lecture 98 Getting started with error handling Section 19: Stock Data API Lecture 99 Stock Data Api Course Intro Lecture 100 Exploring API Lecture 101 Constructing a URL Lecture 102 Fetching Data Lecture 103 Parsing Data Lecture 104 Graphing Data Lecture 105 Stock Data API Course Summary Lecture 106 Wall Street Trader - Fetching and Parsing Stock Data Lecture 107 Source Files - Stock Data API Code Section 20: Technical Stock Analysis Lecture 108 Technical Analysis Course Intro Lecture 109 Learn the Lingo Lecture 110 Buying and Selling Lecture 111 Reading Stock Graphs Lecture 112 Common Technical Indicators Lecture 113 Trading Strategies Lecture 114 Technical Analysis Course Summary Lecture 115 Wall Street Trader - Technical Analysis Section 21: Intro to Tensorflow and Machine Learning Lecture 116 Tensorflow and Machine Learning Course Intro Lecture 117 Intro to Machine Learning Lecture 118 Intro to Tensorflow Lecture 119 Installing Tensforflow Lecture 120 Tensorflow Variable Nodes Lecture 121 Running Graphs with Tensorflow Sessions Lecture 122 Tensorflow Operations Lecture 123 Simple Linear Regression Model Lecture 124 Tensorflow and Machine Learning Course Summary Lecture 125 Wall Street Trader - Tensorflow and ML Lecture 126 Source Files - Tensorflow Practice Section 22: Simple Stock Market Prediciton Lecture 127 Simple Stock Market Prediction Intro Lecture 128 Exploring Stock API Lecture 129 Fetching Stock Data Lecture 130 Creating Datasets Lecture 131 Building the Model Lecture 132 Training and Testing the Model Lecture 133 Simple Stock Prediction Summary Lecture 134 Wall Street Trader - Simple Stock Prediction Lecture 135 Source Files - Simple Stock Prediction Model Section 23: Stock Price Prediction Lecture 136 Stock Price Prediction Course Intro Lecture 137 Intro to Keras Lecture 138 Intro to LSTM Cells Lecture 139 Fecthing and Transforming data Lecture 140 Creating Datasets Lecture 141 Building the Model Lecture 142 Training and Testing the Model Lecture 143 Understanding Model Output Lecture 144 Stock Price Prediction Course Summary Lecture 145 Wall Street Trader - Stock Price Prediction Lecture 146 Source Files - Stock Price Prediction Section 24: Quantopian Lecture 147 Quantopian 101 Course Intro Lecture 148 Intro to Quantopian Lecture 149 Exploring Quantopian Website Lecture 150 Quantopian Pipeline Intro Lecture 151 Fetching Data Lecture 152 Running a Pipeline Lecture 153 Fetching Factors Lecture 154 Applying Filters Lecture 155 Building a Complete Pipeline Lecture 156 Quantopian Algorithm IDE Intro Lecture 157 Algorithm IDE Basics Lecture 158 Making Trades Lecture 159 Conditional Trades Lecture 160 Important Pipelines Lecture 161 Creating and Testing a Portfolio Lecture 162 Quantopian 101 Course Summary Lecture 163 Wall Street Trader - Intro to Quantopian Section 25: Sketch Lecture 164 Course Intro and Sketch Tools Lecture 165 Sketch Files - Sketch Tools Lecture 166 Sketch Basics and Online Resources Lecture 167 Plug-ins and Designing your First Mobile app Lecture 168 Your First Mobile App Continued Lecture 169 Sketch Files - Your First Mobile App Lecture 170 Shortcuts and Extra tips Lecture 171 Sketch Files - Shortcuts by Mammoth Interactive Section 26: Learn to Code in HTML Lecture 172 Intro to HTML Lecture 173 Writing our first HTML Lecture 174 Intro to Lists and Comments Lecture 175 Nested Lists Lecture 176 Loading Images Lecture 177 Loading Images in Lists Lecture 178 Links Lecture 179 Images as Link Lecture 180 Mailto Link Lecture 181 Div Element Section 27: Learn to Code in CSS Lecture 182 Introduction Lecture 183 Introducing the Box Model Lecture 184 Writing our First CSS Lecture 185 More CSS Examples Lecture 186 Inheritance Lecture 187 More on Type Selectors Lecture 188 Getting Direct Descendents Lecture 189 Class Intro Lecture 190 Multiple Classes Lecture 191 id Intro Lecture 192 CSS Specificity Lecture 193 Selecting Multiple Pseudo Classes and Sibling Matching Lecture 194 Styling Recipe Page Lecture 195 Loading External Stylesheet Section 28: D3.js Lecture 196 Introduction to Course and D3 Lecture 197 Source Code Lecture 198 Handling Data and Your First Project Lecture 199 Source code Lecture 200 Continuing your First Project Lecture 201 Understanding Scale Lecture 202 Source Code Lecture 203 Complex charts, Animations and Interactivity Lecture 204 Source Code Section 29: Introduction to PyCharm Lecture 205 Downloading and Installing Pycharm and Python Lecture 206 Support for Python Problems or Questions Lecture 207 Exploring Pycharm Lecture 208 Learning Python with Mammoth Interactive Section 30: Python Language Basics Lecture 209 Intro to Variables Lecture 210 Variables Operations and Conversions Lecture 211 Collection Types Lecture 212 Collections Operations Lecture 213 Control Flow If Statements Lecture 214 While and For Loops Lecture 215 Functions Lecture 216 Classes and Objects Section 31: Flask Lecture 217 Setting Up and Basic Flask Lecture 218 Setting up Terminals on Windows 7 and Mac Lecture 219 Terminal basic commands and symbols Lecture 220 Source Code - Setting up Flask Lecture 221 Source Code - Basic Flask HTML & CSS Lecture 222 Basic Flask Database Lecture 223 Source Code - Basic Flask Database Lecture 224 Flask Session and Resources Lecture 225 Source Code - Flask Session Lecture 226 Flask Digital Ocean Lecture 227 Flask Digital Ocean Continued Section 32: Xcode Fundamentals Lecture 228 Intro and Demo Lecture 229 General Interface Lecture 230 Files System Lecture 231 ViewController Lecture 232 Storyboard File Lecture 233 Connecting Outlets and Actions Lecture 234 Running an Application Lecture 235 Debugging an Application Lecture 236 Source Code and Art Assets Section 33: Swift 4 Language Basics Lecture 237 Language Basics Topics List Section 34: Variable and Constants Lecture 238 Learning Goals Lecture 239 Intro to Variables and Constants Lecture 240 Primitive types Lecture 241 Strings Lecture 242 Nil Values Lecture 243 Tuples Lecture 244 Type Conversions Lecture 245 Assignment Operators Lecture 246 Conditional Operators Lecture 247 Variables and Constants Text.playground Section 35: Collection Types Lecture 248 Topics List and Learning Objectives Lecture 249 Intro to Collection Types Lecture 250 Creating Arrays Lecture 251 Common Array Operations Lecture 252 Multidimensional Arrays Lecture 253 Ranges Lecture 254 Collection Types Text.playground Section 36: Control flow Lecture 255 Topics List and Learning Objectives Lecture 256 Intro to If and Else Statements Lecture 257 Else If Statements Lecture 258 Multiple Simultaneous Tests Lecture 259 Intro To Switch Statements Lecture 260 Advanced Switch Statement Techniques Lecture 261 Testing for Nil Values Lecture 262 Intro to While Loops Lecture 263 Intro to for...in Loops Lecture 264 Intro to For...In Loops (Cont'd) Lecture 265 Complex Loops and Loop Control statements Lecture 266 Control Flow Text.playground Section 37: Functions Lecture 267 Intro to Functions Lecture 268 Function Parameters Lecture 269 Return Statements Lecture 270 Parameter Variations - Argument Labels Lecture 271 Parameter Variations - Default Values Lecture 272 Parameters Variations - InOut Parameters Lecture 273 Parameter Variations - Variadic Parameters Lecture 274 Returning Multiple Values Simultaneously Lecture 275 Functions Text.playground Section 38: Classes, Struct and Enums Lecture 276 Topics List and Learning Objectives Lecture 277 Intro to Classes Lecture 278 Properties as fields - Add to Class Implementation Lecture 279 Custom Getters and Setters Lecture 280 Calculated Properties Lecture 281 Variable Scope and Self Lecture 282 Lazy and Static Variables Lecture 283 Behaviour as Instance Methods and Class type Methods Lecture 284 Behaviour and Instance Methods Lecture 285 Class Type Methods Lecture 286 Class Instances as Field Variables Lecture 287 Inheritance, Subclassing and SuperClassing Lecture 288 Overriding Initializers Lecture 289 Overriding Properties Lecture 290 Overriding Methods Lecture 291 Structs Overview Lecture 292 Enumerations Lecture 293 Comparisons between Classes, Structs and Enums Lecture 294 Classes, Structs, Enums Text.playground Section 39: Practical MacOS BootCamps Lecture 295 Introduction and UI Elements Lecture 296 Calculator Setup and Tax Calculator Lecture 297 Calculate Tax And Tip - Mammoth Interactive Source Code Lecture 298 Tip Calculator and View Controller Lecture 299 View Controller - Mammoth Interactive Source Code Lecture 300 Constraints Lecture 301 Constraints - Mammoth Interactive Source Code Lecture 302 Constraints Code Lecture 303 Refactor Lecture 304 Refactor - Mammoth Interactive Source Code Lecture 305 MacOsElements - Mammoth Interactive Source Code Section 40: Data Mining With Python Lecture 306 Data Wrangling and Section 1 Lecture 307 Project Files - Data Mining with Mammoth Interactive Lecture 308 Project Files - Data Wrangling with Mammoth Interactive Lecture 309 Data Mining Fundamentals Lecture 310 Project Files - Data Mining fundamentals with Mammoth Interactive Lecture 311 Framework Explained, Taming Big Bank with Data Lecture 312 Project Files - Frameworks with Mammoth Interactive Lecture 313 Mining and Storing Data Lecture 314 Project Files - Mining and Storing with Mammoth Interactive Lecture 315 NLP (Natural Language Processing) Lecture 316 Project Files - NLP with Mammoth Interactive Lecture 317 Summary Challenge Lecture 318 Conclusion Files - Mammoth Interactive Section 41: Introduction to Video Editing Lecture 319 Introduction to the Course Lecture 320 Installing Camtasia Lecture 321 Exploring the Interface Lecture 322 Camtasia Project Files Section 42: Setting Up a Screen Recording Lecture 323 Introduction and Tips for Recording Lecture 324 Creating a Recording Account Lecture 325 Full Screen vs Window Mode Lecture 326 Setting the Recording Resolution Lecture 327 Different Resolutions and their Uses Lecture 328 Tips to Improve Recording Quality and Summary Section 43: Camtasia Recording Lecture 329 Introduction and Workflow Lecture 330 Tools Options Menu Lecture 331 Your First Recording Lecture 332 Viewing your Test Lecture 333 Challenge - VIDEO GAME NARRATION Lecture 334 Mic Etiqutte Lecture 335 Project - Recording Exercise Lecture 336 Webcam, Telprompter, and Summary Section 44: Camtasia Screen Layout Lecture 337 Introduction and Tools Panel Lecture 338 Canvas Lecture 339 Zoom N Pan Lecture 340 Annotations Lecture 341 Yellow Snap Lines Lecture 342 TimeLine Basics, Summary and Challenge Section 45: Camtasia Editing Lecture 343 Introduction and Importing Media Lecture 344 Markers Lecture 345 Split Lecture 346 Working with Audio Lecture 347 Clip Speed Lecture 348 Locking and Disabling tracks Lecture 349 Transitions Lecture 350 Working with Images Lecture 351 Voice Narration Lecture 352 Noise Removal Lecture 353 Smart Focus Lecture 354 Summary and Challenge Section 46: Advance Editing Introduction Lecture 355 Advance Editing Introduction Lecture 356 Zooming Multiple Tracks Lecture 357 Easing Lecture 358 Animations Lecture 359 Behaviors Lecture 360 Color Adjustment Lecture 361 Clip Speed Lecture 362 Remove a Color Lecture 363 Device Frame Lecture 364 Theme Manager Lecture 365 Libraries Lecture 366 Media and Summary Section 47: Camtasia Resources and Tips Lecture 367 Resources and Tips Introduction Lecture 368 Masking Lecture 369 Extending Frames Lecture 370 Working with Video Section 48: Exporting a Project for Youtube Lecture 371 Exporting a Project for Youtube Section 49: Code with C# Lecture 372 Introduction to Course and Types Lecture 373 Operator, Classes , and Additional Types Lecture 374 Statements & Loops Lecture 375 Arrays, Lists, and Strings Lecture 376 Files, Directories, and Debugs Lecture 377 Source code Section 50: Learn to Code with R Lecture 378 Intro to R Lecture 379 Control Flow and Core Concepts Lecture 380 Matrices, Dataframes, Lists and Data Manipulation Lecture 381 GGplot and Intro to Machine learning Lecture 382 Conclusion Lecture 383 Source Code Section 51: Advanced R Lecture 384 Course Overview and Data Setup Lecture 385 Source Code - Setting Up Data - Mammoth Interactive Lecture 386 Functions in R Lecture 387 Source Code - Functions - Mammoth Interactive Lecture 388 Regression Model Lecture 389 Source Code - Regression Models - Mammoth Interactive Lecture 390 Regression Models Continued and Classification Models Lecture 391 Source Code - Classification Models - Mammoth Interactive Lecture 392 Classification Models Continued, RMark Down and Excel Lecture 393 Source Code - RMarkDown And Excel - Mammoth Interactive Lecture 394 Datasets - Mammoth Interactive Section 52: Learn to Code with Java Lecture 395 Introduction and setting up Android Studio Lecture 396 Introduction - Encryption Source Code Lecture 397 Setting up Continued Lecture 398 Java Programming Fundamentals Lecture 399 Source Code - Java Programming Fundamentals Lecture 400 Additional Java fundamentals Lecture 401 Source Code - Additional fundamentals Lecture 402 Classes Lecture 403 Source Code - Classes Lecture 404 Please rate this course Lecture 405 Bonus Lecture - Mammoth Interactive Deals This course does not assume any prior coding knowledge.,People interested in finance and investing,Coders who want to specialize in finance,Anyone who wants to learn programming for an in-demand field,Finance professionals who want to learn FinTech Homepage https://www.udemy.com/course/mastering-fintech-and-machine-learning/ Download ( Rapidgator ) https://rapidgator.net/file/0055994ca19ee895e1ec2e61a8c1469c/lnyaw.Mastering.Fintech.And.Machine.Learning.part40.rar.html https://rapidgator.net/file/05809b00f6efda5335c6daf469357bb2/lnyaw.Mastering.Fintech.And.Machine.Learning.part38.rar.html 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  10. Last Updated 08/2022 MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Genre: eLearning | Language: English + srt | Duration: 47 lectures (6h 35m) | Size: 6 GB What is VMware, What are the Benefits, and How to use it! What you'll learn Learn what VMware vSphere, ESXi and vCenter are How to Install and Configure the various VMware Components How to Build and Setup Virtual Machines (VM) How to configure great vCenter features such as vMotion, DRS and HA How to configure the Network and Storage components of VMware ...and Lots Lots more. Requirements Understading of basic IT Administration and Support Basic understanding of what a Computer Network is Description Complete VMWare vSphere ESXi and vCenter Administration Overview - In this course we'll give you an overview of VMware, discussing how to setup VMware vSphere, including ESXi and vCenter. We'll also talk about how you can start setting up and building your own VM's! This course will give the necessary skills to get started and will also act as a valuable reference for your continued VMware learning. If you are new to IT or have been in Technologies for sometime, this course will give you the foundation that you need to either get that IT job, get promoted or improve your existing Tech skillset specifically around the VMware vSphere environment. In this course we'll cover - - What is VMware. - What is vCenter, ESXi and how to use them - How to install, setup and configure your own VMware environment - How to build, configure and manage Virtual Machines (VM's) - How to troubleshoot your environment ** This course is aimed at VMware vSphere 7 administration, however is also relevant to earlier versions of VMware vSphere including v6.7 and v6.5, so videos are spread across versions with all features being available in the newest v7. Do I need to be an expert? No, this course is designed for people who may be starting out in technology, those who are already familiar certain infrastructure technology and those who want to learn more about Virtualization technology, specifically VMware. It'll provide an essential foundation for anyone wanting to learn and become more proficient in VMware. Why this course? This course will be easy to understand, and will give you an overview of the necessary IT Server skills that you need to know. Want to become a VMware, Virtualization or Systems Administrator? Already in IT? It's essential that you understand the VMware virtualization technology. VMware is used extensively by many companies, small, medium and large, so getting a good understanding of VMware will greatly assist you in your IT career! 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  11. Last Updated 08/2022 MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Genre: eLearning | Language: English + srt | Duration: 47 lectures (6h 35m) | Size: 6 GB What is VMware, What are the Benefits, and How to use it! What you'll learn Learn what VMware vSphere, ESXi and vCenter are How to Install and Configure the various VMware Components How to Build and Setup Virtual Machines (VM) How to configure great vCenter features such as vMotion, DRS and HA How to configure the Network and Storage components of VMware ...and Lots Lots more. Requirements Understading of basic IT Administration and Support Basic understanding of what a Computer Network is Description Complete VMWare vSphere ESXi and vCenter Administration Overview - In this course we'll give you an overview of VMware, discussing how to setup VMware vSphere, including ESXi and vCenter. We'll also talk about how you can start setting up and building your own VM's! This course will give the necessary skills to get started and will also act as a valuable reference for your continued VMware learning. If you are new to IT or have been in Technologies for sometime, this course will give you the foundation that you need to either get that IT job, get promoted or improve your existing Tech skillset specifically around the VMware vSphere environment. In this course we'll cover - - What is VMware. - What is vCenter, ESXi and how to use them - How to install, setup and configure your own VMware environment - How to build, configure and manage Virtual Machines (VM's) - How to troubleshoot your environment ** This course is aimed at VMware vSphere 7 administration, however is also relevant to earlier versions of VMware vSphere including v6.7 and v6.5, so videos are spread across versions with all features being available in the newest v7. Do I need to be an expert? No, this course is designed for people who may be starting out in technology, those who are already familiar certain infrastructure technology and those who want to learn more about Virtualization technology, specifically VMware. It'll provide an essential foundation for anyone wanting to learn and become more proficient in VMware. Why this course? This course will be easy to understand, and will give you an overview of the necessary IT Server skills that you need to know. Want to become a VMware, Virtualization or Systems Administrator? Already in IT? It's essential that you understand the VMware virtualization technology. VMware is used extensively by many companies, small, medium and large, so getting a good understanding of VMware will greatly assist you in your IT career! 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  12. Last updated 4/2017 MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz Language: English | Size: 1.98 GB | Duration: 9h 51m See the first steps to building fast and dynamic Android apps employing test-driven development What you'll learn Leverage well known, best practices for Android app development Use the best third-party libraries in the business which are not known to developers at the beginner-intermediate level Understand why test driven design is important Write reusable test components with behavior driven design Use plugins that enhance the testing experience Learn Android-specific test frameworks, including UI tests Requirements Requires basic knowledge of programming in Java. Basic familiarity with the Android environment and ecosystem Description Packt's Video Learning Paths are a series of individual video products put together in a logical and stepwise manner such that each video builds on the skills learned in the video before i Android Nougat is the 7th major version of the Android operating system. Test-driven development enables good design. It only makes sense to adopt it for Android N app development. Sounds interesting? Let's see how easy it is! Nougat introduces notable changes to the operating system and its development platform, including the ability to display multiple apps on-screen at once in a split-screen view, support for inline replies to notifications, an OpenJDK-based Java environment, support for the Vulkan graphics rendering API, and "seamless" system updates on supported devices. Good object-oriented design and test-driven design are complementary and this Learning Path will explain how. This Learning Path covers the fundamentals of app development in Android N including the Android Studio and Android SDK, networking concepts with the API, Firebase analytics and crash analysis, and publishing your application on the Play Store. We will then look in detail how test-driven development can be implemented for building apps in Android. The goal of this Learning Path is to help you build an application for Android Nougat, using the latest features of Android. We will focus on individual app modules and teach you to implement different TDD methods to create reliable and smarter apps in less time. This Learning Path is authored by some of the best in their fields. Soham Mondal Soham Mondal has worked with Android for about 4 years now and his own app Skyro Voice Recorder has around half a million downloads on the Play Store and has been featured there a couple of times. Apart from that, he has consulted with a bunch of start-ups on Android/UX and was an organizer with Blrdroid, one of the largest Android groups in the world. Brandan Jones Brandan Jones has been an Adjunct Assistant Professor for the University of Cincinnati since the 2000-2001 school year. He has taught many courses in programming, from introductory programming to full stack development. Brandan proposed and created the first Android programming course at the University of Cincinnati, and has been teaching it ever since. He reapplied this course and taught it at Northwestern University's School of Continuing Studies as well. Brandan is the creator of the Android app PlantPlaces Mobile, which allows users to search for plants by color, and GPS plants. He wrote this app in 2012, using TDD principles. He has used selected JSON feeds from that app in the examples in this video course. Brandan's mix of both academic and professional experience means that he brings real-world concepts to the classroom. Most of his high level classes include hands on experience with unit testing, scrum, and distributed version control systems. Overview Section 1: Learning Android N Application Development Lecture 1 The Course Overview Lecture 2 Why Android N? Lecture 3 Basics of Android Lecture 4 Anatomy of Our app Lecture 5 Tools Overview Lecture 6 Tools - Android Studio and Emulators Lecture 7 UI Section Overview Lecture 8 Hello World Lecture 9 Home Page Card Lecture 10 Home Page Card Implementation Lecture 11 NewsArticle, Adapters, and RecyclerView Lecture 12 Creating a NewsArticle Lecture 13 Implementing the ArrayAdapter Lecture 14 Implementing the RecyclerView Lecture 15 The Details Page Lecture 16 Event Handling and Navigation Lecture 17 Enabling Navigation Lecture 18 Android N Multiwindow Features Lecture 19 Networking Section Overview Lecture 20 Networking Basics Lecture 21 News API Lecture 22 Parsing the News API Response Lecture 23 Parsing the News API Response - Implementation Lecture 24 Retrofit Lecture 25 Retrofit Implementation Lecture 26 Testing API calls Lecture 27 Connecting the Response to the UI Lecture 28 Analytics and More Lecture 29 Analytics and Crash Reporting Implementation Lecture 30 Addition Attribution Lecture 31 Introduction to Testing in Android Lecture 32 Unit Testing in Android Lecture 33 Unit Testing with Powermock Lecture 34 Instrumentation Testing in Android Lecture 35 Espresso Implementation Lecture 36 Preparing to Upload to the Play Store Lecture 37 Uploading to the Play Store Lecture 38 Best Practices Lecture 39 Review of the Project Section 2: Test-Driven Android Lecture 40 The Course Overview Lecture 41 Why Test-Driven Design? Lecture 42 The Testing Pyramid Lecture 43 Behavior-Driven Development Lecture 44 Android Project Structure Lecture 45 Best Practices - Interfaces, DTOs, and Layers Lecture 46 Why Interfaces? Lecture 47 DTO Best Practices Lecture 48 Layer Description - UI, Business Logic, and Data Access Lecture 49 Minimizing If Tests Lecture 50 JUnit Syntax Lecture 51 JUnit Annotations Lecture 52 Example with Setup and Teardown Lecture 53 Design for Test Lecture 54 Create a Test-driven Design Test Lecture 55 Given, when, and then syntax Lecture 56 Example - Given, When, and Then Lecture 57 Extended Given, When, and Then Test Lecture 58 More Asserts Lecture 59 More Assert Examples Lecture 60 Hamcrest Asserts Lecture 61 Remove Dependencies with Mockito Lecture 62 Mockito Example Lecture 63 Technical Debt Lecture 64 Unit Test Code Coverage in Android Studio Lecture 65 Build environment Lecture 66 Android Instrumentation Test Lecture 67 Android Instrumentation Test Example Lecture 68 Espresso Overview Lecture 69 Example Espresso Test Lecture 70 Firebase Test Lab If you know Java in depth and have built applications with the language but not apps for Android devices, then this Learning Path is for you. Android developers wanting to learn and leverage test-driven development in their app development will also find this Learning Path useful. 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  13. Published 8/2022 MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz Language: English | Size: 496.28 MB | Duration: 0h 59m Learn faster and easier by using the full potential of your imagination and creativity What you'll learn Make learning quicker, easier, and more fun Remember absolutely anything Become fluent in any language quicker Use shortcuts to become an expert in any field Read faster and retain more Requirements No experience required. Just bring your curiosity and thirst for knowledge. Description Change the way you learn and look at the world forever. Reach the pinnacle of your career quicker. Succeed in whatever you do. Get ahead of everyone.The world is changing faster and faster not just every year but every day. Those who are left behind won't be able to cope with this constantly shifting civilization. There will just be too many things to learn and overcome for people to even stay in the fast lane.But if you stay ahead--and enjoy getting there, mind you--you'll reap the rewards. It starts with this course.Look... things don't have to be complex and too difficult for you to overcome--especially when it comes to learning. I have a feeling you want to level up if you're reading this or even if you just clicked on the course!Well, now is the time for you to do so. Remember: Regardless of what people tell you, investing in yourself is the best thing you could do for yourself. It's the greatest favour. So, let's do this!WHAT YOU'LL LEARN:In 3 Modules, you'll learn different techniques and how to apply them to various subjects and situations.MODULE 2:This is the most important and exciting module as you'll break misconceptions about how you're not a genius, how you can't seem to remember a lot of things, and blah blah blah!I teach two general techniques that I will expand upon in module 2. But before the end of this first module, I guarantee you'll already be applying the techniques you've learnt and making them your own! You might even break your own expectations of yourself.MODULE 3:Here's where things get a little interesting. I show you how to apply these techniques, how to twist them, how to combine them, and how to enjoy using them in different areas of your life. MODULE 4:It doesn't end there! Get ready to improve on what you've learnt even more. And get ready to break misconceptions about yourself and change the way you see the world!Don't hold off on investing in yourself and your future--or even your family's future. Take action and join me in getting ahead of the game. The world isn't waiting. It's only getting faster. Overview Section 1: Introduction Lecture 1 Introduction Section 2: The Main Techniques Lecture 2 Mnemonics Lecture 3 Mnemonics Example Lecture 4 Stories Lecture 5 Stories Example Lecture 6 Stories continued Section 3: Subjects and Situations Lecture 7 Read faster and retain more (Lesson 3) Lecture 8 Mind hacks for languages and difficult words (Lesson 4) Lecture 9 Lesson 4 Example Lecture 10 Imaginative note-taking Lecture 11 Make "difficult" subjects fun and easy Lecture 12 Creating masterpieces: The practical and the theoretical Lecture 13 (Continued) Creating masterpieces: The practical and the theoretical Lecture 14 How to kick dancing, martial arts, and sports in the butt! Section 4: Beyond Imagination Lecture 15 Making the complex easy Lecture 16 How you can supercharge your learning with habits Lecture 17 Do you! Lecture 18 The world is at your fingertips Section 5: A Personal Message Lecture 19 A Personal Message Absolutely anyone, especially those who have difficulties learning new things. Homepage https://www.udemy.com/course/stop-drop-and-learn/ Download ( Rapidgator ) https://rapidgator.net/file/f343474aeea02b33cb0eca02c64e468c/sytjp.Imaginative.Learning.rar.html [b]Download (Uploadgig)[/b] https://uploadgig.com/file/download/5b947671D2bA820A/sytjp.Imaginative.Learning.rar Download ( NitroFlare ) https://nitroflare.com/view/66F9EA8248115F3/sytjp.Imaginative.Learning.rar Links are Interchangeable - No Password - Single Extraction
  14. Published 8/2022 MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz Language: English | Size: 2.55 GB | Duration: 7h 36m Build AI agents in Jupyter Notebooks! What you'll learn Build machine learning algorithms Code in Python Trade cryptocurrency automatically Analyze data from Twitter Requirements No experience necessary Description Build a Machine Learning Bot to Trade Based on Social MediaSince 2006, Twitter has been a continuously growing source of information, keeping us informed about all and nothing. It is estimated that more than 6,000 tweets are exchanged on the platform every second, making it an inexhaustible mine of information that it would be a shame not to use.Fortunately, there are different ways to process tweets in an automated way, and retrieve precise information in an instant ... Interested in learning such a solution in a quick and easy way? Take a look belowBy taking this course, you will learn all the steps necessary to build your own Tweet Sentiment prediction model. That said, you will learn much more as the course is separated into 4 different parts, linked together, but providing its share of knowledge in a particular field (Text Mining, NLP and Machine Learning).Alexandra Kropova is a software developer with extensive experience in full-stack web development, app development and game development. She has helped produce courses for Mammoth Interactive since 2016, including the Coding Interview series in Java, JavaScript, C++, C#, Python and Swift.When does the course start and finish? The course starts now and never ends! It is a completely self-paced online course - you decide when you start and when you finish. How long do I have access to the course? How does lifetime access sound? After enrolling, you have unlimited access to this course for as long as you like - across any and all devices you own. Overview Section 1: 00a Course Overview Lecture 1 00 Course Overview Lecture 2 Source Files Section 2: 00b Mammoth Interactive Courses Introduction Lecture 3 00 About Mammoth Interactive Lecture 4 01 How To Learn Online Effectively Lecture 5 Source Files Section 3: 01 Introduction to Python (Prerequisite) Lecture 6 00. Intro To Course And Python Lecture 7 01. Variables Lecture 8 02. Type Conversion Examples Lecture 9 03. Operators Lecture 10 04. Collections Lecture 11 05. List Examples Lecture 12 06. Tuples Examples Lecture 13 07. Dictionaries Examples Lecture 14 08. Ranges Examples Lecture 15 09. Conditionals Lecture 16 10. If Statement Examples Lecture 17 11. Loops Lecture 18 12. Functions Lecture 19 13. Parameters And Return Values Examples Lecture 20 14. Classes And Objects Lecture 21 15. Inheritance Examples Lecture 22 16. Static Members Examples Lecture 23 17. Summary And Outro Lecture 24 Source Files Section 4: 02 Scrape and Process Tweets Lecture 25 01 Get Twitter Developer API Lecture 26 02 Get Latest Tweet Via API Lecture 27 03 Check If Tweeted About Cryptocurrency Lecture 28 Source Files Section 5: 03 Tweet Sentiment Analysis Lecture 29 01 What Is Sentiment Analysis Lecture 30 02 Analyze Tweet Sentiment Lecture 31 Source Files Section 6: 04 Buy Cryptocurrency Algorithmically - Test with Sandbox Lecture 32 01 Get Coinbase Pro Sandbox API Lecture 33 02 Open Coinbase Pro Sandbox Account Via API Lecture 34 03 Test Buy From Coinbase Sandbox Via API Lecture 35 Source Files Section 7: 05 Buy Cryptocurrency Algorithmically - Real Coins Lecture 36 01 Get Coinbase API Lecture 37 02 Buy Cryptocurrency From API Lecture 38 Source Files Section 8: 06 Run Bot All Day Lecture 39 01 Run Bot All Day Lecture 40 Source Files Section 9: 07 Buy Doge with Kraken API Lecture 41 01 How To Access Kraken API Lecture 42 02 Buy Doge Algorithmically Lecture 43 Source Files Section 10: 08 Data Analysis - Other Cryptos Affected by Tweets Lecture 44 00 Project Preview Lecture 45 01 Fetch Crypto Stock Data Lecture 46 02 Visualize Crypto Data Lecture 47 03 Scrape Historical Tweets Lecture 48 04 Filter Tweets About Crypto Only Lecture 49 05 Visualize Tweet Effects On Crypto Value Lecture 50 Source Files Section 11: 09 How to Expand Bot Lecture 51 01 Challenge - How To Expand Bot Lecture 52 Source Files Anyone interested in trading algorithmically with machine learning Homepage https://www.udemy.com/course/build-a-machine-learning-bot-to-trade-based-on-social-media/ Download ( Rapidgator ) https://rapidgator.net/file/0d0d6c9be7543240eeaf47c033cf2785/sifnz.Build.A.Machine.Learning.Bot.To.Trade.Based.On.Social.Media.part3.rar.html https://rapidgator.net/file/21a392b5c15c4393f856dc637422ce56/sifnz.Build.A.Machine.Learning.Bot.To.Trade.Based.On.Social.Media.part2.rar.html https://rapidgator.net/file/9849ef0f6ba4eb9826550e19e8dee351/sifnz.Build.A.Machine.Learning.Bot.To.Trade.Based.On.Social.Media.part1.rar.html [b]Download (Uploadgig)[/b] https://uploadgig.com/file/download/36Fb37db9A851daf/sifnz.Build.A.Machine.Learning.Bot.To.Trade.Based.On.Social.Media.part3.rar https://uploadgig.com/file/download/3fa238e8C7d266Ff/sifnz.Build.A.Machine.Learning.Bot.To.Trade.Based.On.Social.Media.part1.rar https://uploadgig.com/file/download/BfC394194d627B03/sifnz.Build.A.Machine.Learning.Bot.To.Trade.Based.On.Social.Media.part2.rar Download ( NitroFlare ) https://nitroflare.com/view/3200918B58BD476/sifnz.Build.A.Machine.Learning.Bot.To.Trade.Based.On.Social.Media.part1.rar https://nitroflare.com/view/4647904450B8A68/sifnz.Build.A.Machine.Learning.Bot.To.Trade.Based.On.Social.Media.part3.rar https://nitroflare.com/view/98C12BD9FD59508/sifnz.Build.A.Machine.Learning.Bot.To.Trade.Based.On.Social.Media.part2.rar Links are Interchangeable - No Password - Single Extraction
  15. Published 8/2022 MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz Language: English | Size: 2.37 GB | Duration: 6h 58m There's NO better way to spend your free time than to learn how to build practical projects What you'll learn Combinatorics For Probability Calculate Center Of Distribution Distributions in Machine Learning Machine Learning Optimization Requirements No experience necessary Description Buff your skills to keep your job and get a raise in ANY economic climate. This course BUNDLE keeps your skills sharp and your paycheque up!Probability and Statistics for Machine LearningDistributions in Machine LearningMachine Learning OptimizationThis masterclass is without a doubt the most comprehensive course available anywhere online. Even if you have zero experience, this course will take you from beginner to professional.Frequently Asked QuestionsHow do I obtain a certificate?Each certificate in this bundle is only awarded after you have completed every lecture of the course.Many of our students post their Mammoth Interactive certifications on LinkedIn. Not only that, but you will have projects to show employers on top of the certification.Is this an eBook or videos?The majority of this course bundle will be video tutorials (screencasts of practical coding projects step by step.) We will also have several PDFs and all source code.Can't I just learn via Google or YouTube?This bundle is much more streamlined and efficient than learning via Google or YouTube. We have curated a massive 5-course curriculum to take you from absolute beginner to starting a high-paying career.How will I practice to ensure I'm learning?With each section there will be a project, so if you can build the project along with us you are succeeding. There is also a challenge at the end of each section that you can take on to add more features to the project and advance the project in your own time.Mammoth Interactive is a leading online course provider in everything from learning to code to becoming a YouTube star. Mammoth Interactive courses have been featured on Harvard's edX, Business Insider and more. Founder and CEO John Bura has been programming since 1997 and teaching since 2002. John has created top-selling applications for iOS, Xbox and more. John also runs SaaS company Devonian Apps, building efficiency-minded software for technology workers like you. Try a course today. Overview Section 1: Introduction Lecture 1 Introduction Section 2: 01 (Prerequisite) Introduction to Machine Learning Lecture 2 00A What Is Machine Learning Lecture 3 00B Types Of Machine Learning Models Lecture 4 00C What Is Supervised Learning Lecture 5 01 How Does A Machine Learning Agent Learn Lecture 6 02 What Is Inductive Learning Section 3: 02 (Prerequisite) Introduction to Python Lecture 7 00. Introduction Section 4: 02 - 01 Code Python on the Web Lecture 8 02.01 What is Google Colab Lecture 9 02.02 What If I Get Errors Lecture 10 02.03 How Do I Terminate a Session Section 5: 02 - 02 Python Language Fundamentals Lecture 11 02. Variables Lecture 12 03. Type Conversion Examples Lecture 13 04. Operators Lecture 14 05. Operators Examples Lecture 15 06. Collections Lecture 16 07. Lists Lecture 17 08. Multidimensional List Examples Lecture 18 09. Tuples Examples Lecture 19 10. Dictionaries Examples Lecture 20 11. Ranges Examples Lecture 21 12. Conditionals Lecture 22 13. If Statement Examples Lecture 23 14. If Statement Variants Examples Lecture 24 15. Loops Lecture 25 16. While Loops Examples Lecture 26 17. For Loops Examples Lecture 27 18. Functions Lecture 28 19. Functions Examples Lecture 29 20. Parameters And Return Values Examples Lecture 30 21. Classes And Objects Lecture 31 22. Classes Example Lecture 32 23. Objects Examples Lecture 33 24. Inheritance Examples Lecture 34 25. Static Members Example Lecture 35 26. Summary And Outro Section 6: 03 Probability and Statistics for Machine Learning Lecture 36 01 Probability And Information Theory Overview Lecture 37 02 Combinatorics For Probability Lecture 38 03 Law Of Large Numbers Lecture 39 04 Calculate Center Of Distribution Section 7: 04 Distributions in Machine Learning Lecture 40 01 Uniform Distribution Lecture 41 02 Gaussian Distribution Lecture 42 03 Log-Normal Distribution Lecture 43 04 Exponential Distribution Lecture 44 05 Laplace Distribution Lecture 45 06 Binomial Distribution Lecture 46 07 Multinomial Distribution Lecture 47 08 Poisson Distribution Section 8: 05 Machine Learning Optimization Lecture 48 01 Calculate Error Of Machine Learning Model Anyone who needs to learn the fundamentals required for machine learning Homepage https://www.udemy.com/course/probability-and-statistics-for-machine-learning/ Download ( Rapidgator ) https://rapidgator.net/file/46784568647811d69c09adab2290cc83/prmsh.Probability.And.Statistics.For.Machine.Learning..Udemy.part2.rar.html https://rapidgator.net/file/49c4634ab36dff338365e808af4fb063/prmsh.Probability.And.Statistics.For.Machine.Learning..Udemy.part1.rar.html https://rapidgator.net/file/5bfbccd6e0cd36d31229b67344583424/prmsh.Probability.And.Statistics.For.Machine.Learning..Udemy.part3.rar.html [b]Download (Uploadgig)[/b] https://uploadgig.com/file/download/5736019Cf1c4b3Df/prmsh.Probability.And.Statistics.For.Machine.Learning..Udemy.part3.rar https://uploadgig.com/file/download/95d225c7daC8707c/prmsh.Probability.And.Statistics.For.Machine.Learning..Udemy.part2.rar https://uploadgig.com/file/download/B5E760a376b78df9/prmsh.Probability.And.Statistics.For.Machine.Learning..Udemy.part1.rar Download ( NitroFlare ) https://nitroflare.com/view/8157E8950D1A2A6/prmsh.Probability.And.Statistics.For.Machine.Learning..Udemy.part3.rar https://nitroflare.com/view/ED3C7D5DC50F932/prmsh.Probability.And.Statistics.For.Machine.Learning..Udemy.part2.rar https://nitroflare.com/view/FC7F13DEB306E0D/prmsh.Probability.And.Statistics.For.Machine.Learning..Udemy.part1.rar Links are Interchangeable - No Password - Single Extraction
  16. Linkedin Learning Duration: 1h 8m | Video: 1280x720 30fps | Audio: AAC, 48 kHz, 2ch | Size: 594 MB Genre: eLearning | Language: English Machine learning as a concept has been around for over 60 years, but as artificial intelligence becomes more and more popular, there's increased opportunity in the field of artificial intelligence and its subgroups, machine learning and deep learning. And with the explosion of cloud computing, it's only natural to study machine learning with cloud technologies like Azure. In this introductory course to her Azure machine learning series, Zarina Meeran starts you off with the basics of AI, and covers how ML and DL subgroups fit into the picture. She then dives into the various machine learning problems and the machine learning algorithms used to solve these problems. Zarina also covers the machine learning lifecycle to get the end-to-end picture, as well as the tools offered from Azure. Finally, she goes through the architecture of MLOps within the cloud as this is currently adopted. https://www.linkedin.com/feed/ Download ( Rapidgator ) https://rapidgator.net/file/8638c85e7bd2b894b6bad9bb1cab319c/xntdy.A.M.L.D.P.1.rar.html [b]Download (Uploadgig)[/b] https://uploadgig.com/file/download/7d0cf0d87E4Ccd69/xntdy.A.M.L.D.P.1.rar Download ( NitroFlare ) https://nitroflare.com/view/69D281506B1D1B1/xntdy.A.M.L.D.P.1.rar Links are Interchangeable - No Password - Single Extraction
  17. Published 8/2022 MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz Language: English | Size: 900.51 MB | Duration: 1h 6m Syllable Breakdown What you'll learn Identify and pronounce words with vowel/consonant blends. Gain tools to break down words with multiple syllables. Learn the most common prefixes. Learn the most common suffixes. Requirements Students must know how to read words with one single-letter sounds. Students must know their vowels. Description This module contains 6 lessons. This course involves one of the most important lessons--breaking up multisyllabic words. As you transition from initial readings of simple sentences and enter into complex text that contains multiple syllable words, you will need this skill to help decode and pronounce larger words. Every vowel or vowel combination within a word represents a syllable. A syllable is a single, unbroken sound of a spoken (or written) word. Syllables usually contain a vowel and accompanying consonants. A single vowel is sometimes its own syllable.The number of times you hear a vowel (a, e, i , o, u) in a word is equal to the number of syllables a word has. A good way to identify syllables is to think about whether you need to change your mouth shape to say the next bit of the word / the new syllable.This course allows the student to learn to read American English within a short period of time. It is created by a top teacher with years of experience. I have a 95-100% success rate.Within this lesson, you will have multiple opportunities to practice what you've learned. If you follow what is requested in the videos, by the end of Lesson 21, you will be able to read fluently and correctly. Overview Section 1: Module 3: Syllable Breakdown and Blending Lecture 1 Lesson 11: Blending with Vowel/Consonant Blends Lecture 2 Lesson 12: Syllable Breakdown Lecture 3 Lesson 13: Most Common Sounds - List 4 (Common Prefixes) Lecture 4 Lesson 14: Blending with Prefixes Lecture 5 Lesson 15: Most Common Sounds - List 5 (Common Suffixes) Lecture 6 Lesson 16: Blending with Suffixes This is for students that can read basic letters, but have problems with multiple syllable words. Homepage https://www.udemy.com/course/learning-to-read-english-module-3/ Download ( Rapidgator ) https://rapidgator.net/file/dd9c6d8a564bd1ab8298a1c9b740dc58/wzljj.Learning.To.Read.English..Module.3.Of.4.Syllables.rar.html [b]Download (Uploadgig)[/b] https://uploadgig.com/file/download/440bAE308B72a0c3/wzljj.Learning.To.Read.English..Module.3.Of.4.Syllables.rar Download ( NitroFlare ) https://nitroflare.com/view/7AE7C983FC4558F/wzljj.Learning.To.Read.English..Module.3.Of.4.Syllables.rar Links are Interchangeable - No Password - Single Extraction
  18. Last updated 8/2022 MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz Language: English | Size: 811.71 MB | Duration: 0h 58m Most Common Blended Sounds What you'll learn Learn the sounds of consonant blends. Learn how to blend consonant blends in order to pronounce words. Learn the sounds of vowel combinations. Learn how to blend vowel combinations in order to pronounce words. Requirements You will need to know all single-letter sounds of the alphabet. Description This module contains 5 lessons. This course allows the student to learn to read American English within a short period of time. It is created by a top teacher with years of experience. This course follows phonics with the incorporation of common sight words. It is fast, engaging, and uses multi-sensory components. I created this course to help those who want to learn to read in an easy, quick way. I was previously the top teacher in my state for levels of growth in my students. I am currently a literacy trainer. I have been working with my program since 2015. My program allows a nonreader or lagging reader in grades 3-12 and adults to read in 21 hours or less. I have a 95-100% success rate.The program starts out with the easier lessons and graduates into more complex lessons. You will start out building your foundation with single letter sounds, followed by blending those letters to read words. This is the most important start to reading. Next, you will have lessons that teach you blended sounds-some may look familiar, while many will not. For each blended sound lesson, you will learn how to read words with what you've learned and read words within sentences to boost your fluency. It is OK to re-do lessons you have difficulty with. After all, the core of all learning is repetition. Overview Section 1: Module 3: Most Common Sounds - List 1, 2 Lecture 1 Lesson 6: Most Common Sounds - List 1 (Consonant Blends) Lecture 2 Lesson 7: Blending with Consonant Blends Lecture 3 Lesson 8: Most Common Sounds - List 2 (Vowel Combinations) Lecture 4 Lesson 9: Blending with Vowel Combinations Lecture 5 Lesson 10: Most Common Sounds - List 3 (Vowel/Consonant Blends) Beginning and Developing readers Homepage https://www.udemy.com/course/readmodule2/ Download ( Rapidgator ) https://rapidgator.net/file/5ba1a96f65758afe39b5f710dc902d7d/kqtgb.Learning.To.Read.English..Module.2.Of.4.rar.html [b]Download (Uploadgig)[/b] https://uploadgig.com/file/download/1056986cbc7d5040/kqtgb.Learning.To.Read.English..Module.2.Of.4.rar Download ( NitroFlare ) https://nitroflare.com/view/DDD0463D14DA2BE/kqtgb.Learning.To.Read.English..Module.2.Of.4.rar Links are Interchangeable - No Password - Single Extraction
  19. Published 8/2022 MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz Language: English | Size: 2.14 GB | Duration: 4h 21m a workshop to learn the basics of Esri's new offerings in ArcGIS Pro What you'll learn How to define a spatial problem, and plan out the approach for solving it You will learn the differences between ArcMap and ArcGIS Pro You will get a basic overview of the ArcGIS Pro interface How to use ArcGIS Pro to solve our GIS problem How to use Model Builder in ArcGIS Pro to solve our GIS problem How to use Python within ArcGIS Pro to solve our GIS problem Requirements You need a Windows, 64bit PC This is going to be a very hands-on workshop using Esri's ArcGIS Pro. To successfully complete the workshop, you should be able to do the following Organize and locate files on your compute Download and save files from the Internet to your computer (.zip files) Download and install Esri's ArcGIS Pro software. Description As you probably know, Esri is moving their users to the latest software, ArcGIS Pro. Perhaps you are a little hesitant in making that leap. Or, maybe you want to learn how to use different approaches to solve a GIS problem including the GUI, Model Builder, Python scripting, or a 3rd party extension that uses SQL. Or, maybe you want to be able to articulate the strengths and limitations of the different Esri approaches. Whether you are moving to the new Esri platform, of just trying to gain the necessary skills to land that next job in your career, this course will help you get there.In this course, we are going to explore 4 different ways to solve a GIS problem using Esri software: the ArcGIS Pro graphical user interface (GUI), Model Builder, Python Scripting with Arcpy, and spatial SQL with SQL for ArcGIS Pro. As a bonus, I'm also going to introduce you to some of the cloud based solutions that Esri has available.As our base scenario, we are going to perform a GIS analysis to evaluate access to COVID-19 vaccination sites for different ethnic populations in the State of Maryland. Believe it or not, the simple question of what percentage of the population is within a specified distance of a vaccination center is trickier than you'd think, requiring a number of steps to complete.Fortunately, the tools in Esri's ArcGIS Pro allow us to accomplish this task in many different ways. So, you'll not only learn how to use the different approaches, you'll also have a good understanding of the differences among the solutions. It's one thing to be introduced to the different options, and being able to parrot back the strengths and weaknesses of each approach. But, it's another thing to have the actual hands on experience in doing it. As you follow along with me, using the data I provide you, you'll be able to say I have actually used these tools in ArcGIS Pro, and from experience can tell you the strengths and weaknesses of each approach. In the videos, we'll also discuss the appropriateness of each tool, given the particular problem you may be facing. Overview Section 1: Introduction to the class, and getting familiar with ArcGIS Pro Lecture 1 Welcome Lecture 2 Course resources, don't miss this. Lecture 3 Why you should move to ArcGIS Pro Lecture 4 Starting up ArcGIS Pro - what the experience looks like Section 2: Introduction to the Workshop Lecture 5 Data and Problem Lecture 6 Conceptual steps to solve the problem Section 3: Solutions with the ArcGIS Pro GUI Lecture 7 Solutions with the ArcGIS Pro GUI Overview Lecture 8 Step 1: Adding Data Lecture 9 Steps 2 and 3: Select Census Blocks, Join Data Lecture 10 Steps 4 - 6: Summarizing and rejoining our data Lecture 11 Steps 7 - 9: Adding fields, performing calculations, and joining results Lecture 12 Bonus Feature: As the crow flies vs. how the car drives Section 4: Solutions with Model Builder Lecture 13 Solutions with Model Builder Introduction Lecture 14 Overview of the process running the model Lecture 15 Part 1 - Creating the model Lecture 16 Finishing the model Lecture 17 Expanding the model Section 5: Solution with ArcPy Lecture 18 Introduction to the solution with Arcpy Lecture 19 Python introduction Lecture 20 Python in ArcGIS Pro Lecture 21 Writing code to solve our problem Lecture 22 Finishing our program and adding sophistication Section 6: SQL for ArcGIS Pro Lecture 23 Introduction to the SQL for ArcGIS Pro product Lecture 24 Introduction to SQL for ArcGIS Pro Lecture 25 Getting and Starting Manifold GIS Viewer Lecture 26 What is SQL, and why is it good for GIS professionals to learn? 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  20. Published 08/2022 Genre: eLearning | MP4 | Video: h264, 1280x720 | Audio: AAC, 48.0 KHz Language: English | Size: 2.10 GB | Duration: 10 lectures • 4h 28m Comparison of Manual and Automated Testing through Test Plan and Execution What you'll learn To understand the usefulness of software testing and comprehend different testing types To use appropriate methods to test web and desktop applications To differentiate between manual and automated testing To learn different automated testing tools To develop and execute a test plan Requirements No prior programming or testing experience needed You will learn how to develop and execute a test plan Description The course focuses on the basics in software testing methodologies. Students will explore the importance of software testing, why we need to carry out software testing, its relation with software quality and its place within the software development life cycle. They will be introduced with different types of software testing such as White box, black box and gray box testing. They will be introduced to the concept of automated software testing through ATLM - Automated Software Testing Lifecycle Methodology. A couple of automated testing tools such as Selenium and WebLoad will be taught as well. Concepts related to different stages of testing such as unit testing, regression testing, integration testing and acceptance testing are also introduced. They will be taught different phases of Software Testing Lifecycle - STLC. In the first phase of STLC, students will learn different techniques of requirements gathering and how to create a requirements traceability matrix - RTM. Then they will learn about test strategy and test planning. They will learn how to create, manage and execute a test plan. In the next phase, students will be taught how to write test cases, both for functional and non-functional testing. A template will be provided for this purpose. They will be taught how automated software testing lifecycle is different from a traditional testing lifecycle. Who this course is for This course is intended for students who want to learn software testing procedure and get familiar with some automated testing tools such as Selenium, Webload etc. Homepage https://www.udemy.com/course/software-testing-o/ Download ( Rapidgator ) https://rapidgator.net/file/b416a68b07120887b85f034ba490b85f/njkmu.Learning.Software.Testing.A.beginners.guide.part2.rar.html https://rapidgator.net/file/bdb20834cb8c00400bc6dafe57a3c1c2/njkmu.Learning.Software.Testing.A.beginners.guide.part3.rar.html https://rapidgator.net/file/cd950a527c4467fd1dbff1fdd1f16801/njkmu.Learning.Software.Testing.A.beginners.guide.part1.rar.html [b]Download (Uploadgig)[/b] https://uploadgig.com/file/download/345fD6f8E870e290/njkmu.Learning.Software.Testing.A.beginners.guide.part3.rar https://uploadgig.com/file/download/5b233ccC535b284E/njkmu.Learning.Software.Testing.A.beginners.guide.part2.rar https://uploadgig.com/file/download/fb1359272dE1ca57/njkmu.Learning.Software.Testing.A.beginners.guide.part1.rar Links are Interchangeable - No Password - Single Extraction
  21. Last updated 6/2017 MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz Language: English | Size: 2.22 GB | Duration: 10h 54m Develop interesting games progressively using the powerful Unity engine and the 3D computer graphics software-Blender What you'll learn Understand the foundations of Unity Work confidently in the Unity interface Understand Level Design tools Work confidently with C# scripts, functionality, and coding behaviors Familiarize yourself with the best practices of Unity 5.x Get to know several best practices for component-based designs Build the game environment from scratch by constructing the terrain and props, and eventually put it all together to form a scene Create particles and visual effects to enhance the overall visual aesthetic Deploy the game for various types of platforms Requirements This is for absolute beginners. No prior knowledge of Unity or Blender is required. Description Do you want to move from just playing games to developing them? Do you wish to play the games created by you? Unity 5 has become the leader among game development engines. Blender is known in the 3D graphics world as the open-source tool of choice for generating graphical products. Blender and Unity stand out from the crowd as a powerful combination that allows small-to-no budget indie developers or hobbyists alike to develop games that they have always dreamt of creating. Game Development with Unity and Blender is Packt's Video Learning Path that is a series of individual video products put together in a logical and stepwise manner such that each video builds on the skills learned in the video before it. This Learning Path first introduces the Unity engine. It shows how to use the interface and how to build levels, and culminates in the creation of a simple game. The core features and fundamentals are explored in a fun and practical way, encouraging the development of real-world projects while establishing a solid understanding of game development principles. Develop your Unity skills further by exploring scripting and gameplay mechanics. You'll understand the fundamentals of using C# scripts in Unity to build valuable gameplay elements, such as timers and moving objects. Then, you'll move onto building a solid foundation for engineering more complex behaviors. Finally, learn how to implement game logic and basic artificial intelligence, and deploy the game for others to play. The goal of this course to help you master the skills required to develop your dream game from scratch.. About the Authors: This Learning Path is authored by some of the best in the field. Alan Thorn is a multidisciplinary game developer, author, and educator with industry experience of 17 years. He makes games for PC desktop, mobile, and VR. He founded Wax Lyrical Games and created the award-winning Baron Wittard: Nemesis of Ragnarok game, working as designer, programmer, and artist. Lee Zhi Eng is a 3D artist-turned-programmer who is currently the co-founder cum chief technical executive at Reonyx Tech, a technology firm based in Malaysia. Before he co-founded the company, he worked as an artist and programmer in several game studios before becoming a part-time lecturer for two years at a university, teaching game development subjects related to Unity Engine and Unreal Engine. Overview Section 1: Unity 5 for Beginners Lecture 1 Course Overview Lecture 2 Downloading Unity Lecture 3 The Download Archive Lecture 4 Installing Unity Lecture 5 Creating New Projects Lecture 6 User Interface Basics Lecture 7 The Asset Store Lecture 8 Exploring the Example Project Lecture 9 Viewport Navigation Lecture 10 Creating GameObjects Lecture 11 Prototyping Assets Lecture 12 Object Manipulation Lecture 13 Global and Local Space Lecture 14 Object Hierarchies Lecture 15 Import Custom Assets Lecture 16 Exporting Mesh Assets from Blender Lecture 17 Maximization Trick Lecture 18 Using the Game Tab for Play-Testing Lecture 19 Play Mode Versus Edit Mode Lecture 20 Component Based Design Lecture 21 Building a Custom Object Lecture 22 Creating Unity Project Lecture 23 Exploring the Project Folder Lecture 24 Establishing a Level Floor Lecture 25 Project Organization Lecture 26 Creating World Bounds Lecture 27 Level Design Lecture 28 Starting a Coin Object Lecture 29 Creating a Coin Material Lecture 30 Working with Prefabs Lecture 31 Organizing a Scene Lecture 32 Getting Started with Scripting Lecture 33 MonoDevelop and Script Attaching Lecture 34 Object Tagging Lecture 35 Exploring the CountDown Script Lecture 36 Creating Spinning Coins Lecture 37 Using Particle Systems Section 2: Unity 5 Scripting and Gameplay Mechanics Lecture 38 The Course Overview Lecture 39 Configuring Unity and MonoDevelop for Scripting Lecture 40 Creating a Hello World Program Lecture 41 Using the Unity Scripting Reference Lecture 42 Preparing to Create a Mover Script Lecture 43 Positioning an Object through Script Lecture 44 Moving an Object through Script Lecture 45 Working with Vectors and Motion Lecture 46 Using DeltaTime Lecture 47 Creating a Rotator Script Lecture 48 Play Mode and Debugging Lecture 49 Download Unity Lecture 50 Creating a Coin Prefab Lecture 51 Creating Coin Rotation Lecture 52 Creating a Coin Collection Mechanic Lecture 53 Triggers and Collisions Lecture 54 Creating a Timer Lecture 55 Create a User Interface Lecture 56 Use Text Object to Display Countdown Lecture 57 Handle the Win Condition Lecture 58 Starting a Follow Script Lecture 59 Looking at Other Objects Lecture 60 Complete NPC Mover Lecture 61 Detect Player Click Input Lecture 62 Create Raycasts and Intersections Lecture 63 Codeless Clicking Lecture 64 Building a Generic Trigger Action Script Lecture 65 Change Scenes Lecture 66 Player Movement Lecture 67 Player Character and Physics Section 3: Building a Game with Unity and Blender Lecture 68 The Course Overview Lecture 69 Job Roles in Game Development Lecture 70 Game's Story and Visual Style Lecture 71 Characters and Environment Concept Lecture 72 Downloading Blender Lecture 73 Creating the Monster's 3D Model Lecture 74 Unwrapping the Monster's UV Map Lecture 75 Creating the Monster's Texture Lecture 76 Creating the Player Character's 3D Model Lecture 77 Unwrapping the Player Character's UV Map Lecture 78 Character Rigging and Monster's Armature Creation Lecture 79 Creating the Player Character's Armature Lecture 80 Weight Painting Lecture 81 Animating Characters Lecture 82 Building Terrain and Wall Models Lecture 83 Building Rock Models Lecture 84 Creating Rock and Wall Textures Lecture 85 Building Grass Models Lecture 86 Creating the Grass Texture Lecture 87 Basic User Interface of Unity Lecture 88 Importing Environment Assets Lecture 89 Importing Character Assets Lecture 90 Game Structure Design and the Game Flow Lecture 91 Designing the User Interface Structure Lecture 92 Player Inputs and Character Movements Lecture 93 Creating Basic Artificial Intelligence Lecture 94 Creating character attributes Lecture 95 Adding In-game Items and Power-ups Lecture 96 Improving Enemy AI Lecture 97 Adding Save Points Lecture 98 A Basic Particle System Lecture 99 Mist Particles Lecture 100 Torch Fire Lecture 101 Image FX Lecture 102 Quality Settings Lecture 103 Building Settings Lecture 104 Player Settings This Learning Path is for anyone who wants to learn how to develop their own games using Blender and Unity. Homepage https://www.udemy.com/course/learning-path-game-development-with-unity-and-blender/ Download ( Rapidgator ) https://rapidgator.net/file/70c93d448443f3e59337c7bfcf9e6e1f/jufjb.Learning.Path.Game.Development.With.Unity.And.Blender.part3.rar.html https://rapidgator.net/file/925a83a7a9123c8a75695ee7753b7499/jufjb.Learning.Path.Game.Development.With.Unity.And.Blender.part2.rar.html https://rapidgator.net/file/aac0a0620d07178340ffb82e3f1adc88/jufjb.Learning.Path.Game.Development.With.Unity.And.Blender.part1.rar.html [b]Download (Uploadgig)[/b] https://uploadgig.com/file/download/03b9cd147c786d99/jufjb.Learning.Path.Game.Development.With.Unity.And.Blender.part1.rar https://uploadgig.com/file/download/7501c91EabCb96Ba/jufjb.Learning.Path.Game.Development.With.Unity.And.Blender.part3.rar https://uploadgig.com/file/download/7b6F1964d4d84A01/jufjb.Learning.Path.Game.Development.With.Unity.And.Blender.part2.rar Download ( NitroFlare ) https://nitroflare.com/view/3A9A08533EF0DF5/jufjb.Learning.Path.Game.Development.With.Unity.And.Blender.part1.rar https://nitroflare.com/view/5D5D5339EEA2EFA/jufjb.Learning.Path.Game.Development.With.Unity.And.Blender.part2.rar https://nitroflare.com/view/B9E271FC349BCE4/jufjb.Learning.Path.Game.Development.With.Unity.And.Blender.part3.rar Links are Interchangeable - No Password - Single Extraction
  22. Last Update: 4/2021 Duration: 4h 36m | Video: .MP4, 1280x720 30 fps | Audio: AAC, 48 kHz, 2ch | Size: 2 GB Genre: eLearning | Language: English Learn to create Machine Learning Algorithms in Python Data Science enthusiasts. Code templates included. What you'll learn Master Machine Learning on Python Make accurate predictions Make robust Machine Learning models Use Machine Learning for personal purpose Have a great intuition of many Machine Learning models Know which Machine Learning model to choose for each type of problem Use SciKit-Learn for Machine Learning Tasks Make predictions using linear regression, polynomial regression, and multiple regression Classify data using K-Means clustering, Support Vector Machines (SVM), KNN, Decision Trees, Naive Bayes, etc. Requirements Some basic python programming experience. Basic understanding of python libraries like numpy, pasdas and matplotlib.(Optional) Some high school mathematics. Description Interested in the field of Machine Learning? Then this course is for you! This course has been designed by Code Warriors the ML Enthusiasts so that we can share our knowledge and help you learn complex theories, algorithms, and coding libraries in a simple way. We will walk you step-by-step into the World of Machine Learning. With every tutorial, you will develop new skills and improve your understanding of this challenging yet lucrative sub-field of Data Science. This course is fun and exciting, but at the same time, we dive deep into Machine Learning. It is structured the following way You can do a lot in 21 Days. Actually, it's the perfect number of days required to adopt a new habit! What you'll learn:- 1.Machine Learning Overview 2.Regression Algorithms on the real-time dataset 3.Regression Miniproject 4.Classification Algorithms on the real-time dataset 5.Classification Miniproject 6.Model Fine-Tuning 7.Deployment of the ML model Who this course is for Anyone interested in Machine Learning. Students who have at least high school knowledge in math and who want to start learning Machine Learning. Any intermediate level people who know the basics of machine learning, including the classical algorithms like linear regression or logistic regression, but who want to learn more about it and explore all the different fields of Machine Learning. Any people who are not that comfortable with coding but who are interested in Machine Learning and want to apply it easily on datasets. Any students in college who want to start a career in Data Science. Any people who want to create added value to their business by using powerful Machine Learning tools. Homepage https://www.udemy.com/course/learn-machine-learning-in-21-days Download ( Rapidgator ) https://rapidgator.net/file/54e2f70e62d08c5bca0b6939292e3da4/qrgmy.L.M.L.i.21.D.rar.html [b]Download (Uploadgig)[/b] https://uploadgig.com/file/download/64cBb876F3e96309/qrgmy.L.M.L.i.21.D.rar Download ( NitroFlare ) https://nitroflare.com/view/43F9FAB250A3BD5/qrgmy.L.M.L.i.21.D.rar Links are Interchangeable - No Password - Single Extraction
  23. Duration: 2h 6m | Video: .MP4, 1280x720 30 fps | Audio: AAC, 48 kHz, 2ch | Size: 206 MB Genre: eLearning | Language: English This course will introduce you to the concepts needed to identify use-cases for Machine Learning, formulate an ML problem, enumerate the canonical problems that ML is used to solve, and detail how ML is applied to complex data such as text, images and speech. What you'll learn Machine Learning algorithms have the ability to adapt and learn from past experiences. Machine learning is important because of its wide range of applications and its incredible ability to adapt and provide solutions to complex problems. In this course, Key Concepts Machine Learning, you will learn to identify use-cases where ML can provide an appropriate solution, and recognize common structures in ML-based solutions. First, you will explore the limitations of rule-based approaches and how ML mitigates them. Then, you will discover the different types of ML models such as traditional models and representation models and see how you can develop the ML mindset to find solutions to meet your use case. Next, you will explore common ML use cases such as regression, classification, clustering, and dimensionality reduction and learn the differences between supervised and unsupervised learning. You will also study specialized use cases such as recommendation systems, association rules learning, and reinforcement learning, as well as learning to apply ML to complex data such as text, images, and speech data. Finally, you will learn how to formulate your use-case into one of these problem types so that it can then be solved with a commonly used ML-based approach. When you are finished with this course, you will have the skills and knowledge of the conceptual underpinnings of Machine Learning needed to recognize use-cases for ML, and adopt common ML approaches. https://pluralsight.com/ Download ( Rapidgator ) https://rapidgator.net/file/43aa49f1398d958b3a6ed6b1cfb16bc2/jehbi.K.C.M.L.rar.html [b]Download (Uploadgig)[/b] https://uploadgig.com/file/download/C47cfad8557d8337/jehbi.K.C.M.L.rar Download ( NitroFlare ) https://nitroflare.com/view/309FB464218E8F3/jehbi.K.C.M.L.rar Links are Interchangeable - No Password - Single Extraction
  24. Published 08/2022 MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Genre: eLearning | Language: English | Duration: 46 lectures (3h 57m) | Size: 887.1 MB Master the most popular data science and machine learning algorithms in Python (linear regression, logistic...). What you'll learn Implement all our models from scratch, step by step. You will learn every detail of their theory and practice. Fundamentally understand the most popular machine learning algorithms. Master the main machine learning libraries in Python: scikit-learn, numpy, pandas, matplotlib, etc. Understand the data science workflow and how to solve a prediction problem from beginning to end. Diagnose and solve problems in our models. You'll be the person your colleagues will seek when their models fail. Requirements Basic knowledge of python (variables, loops, classes, etc) Experience with pandas and visualization tools helps, but is not required. Description Why study data science? Companies have a problem: they collect and store huge amounts of data on a daily basis. The problem is that they don't have the tools and capabilities to extract knowledge and make decisions from that data. But that is changing. For some years now, the demand for data scientists has grown exponentially. So much so, that the number of people with these skills is not enough to fill all the job openings. A basic search on Glassdoor or Indeed will reveal to you why data scientist salaries have grown so much in recent years. Why this course? Almost every course out there is either too theoretical or too practical. University courses don't usually develop the skills needed to tackle data science problems from scratch, nor do they teach you how to use the necessary software fluently. On the other hand, many online courses and bootcamps teach you how to use these techniques without getting a deep understanding of them, going through the theory superficially. Our course combines the best of each method. On the one hand, we will look at where these methods come from and why they are used, understanding why they work the way they do. On the other, we will program these methods from scratch, using the most popular data science and machine learning libraries in Python. Only when you have understood exactly how each algorithm works, we will learn how to use them with advanced Python libraries. Course content Introduction to machine learning and data science. Simple linear regression. We will learn how to study the relationship between different phenomena. Multiple linear regression. We will create models with more than one variable to study the behavior of a variable of interest. Lasso regression. Advanced version of multiple linear regression with the ability to filter the most useful variables. Ridge regression. More stable version of multiple linear regression. Logistic regression. Most popular classification and detection algorithm. It will allow us to study the relationship between different variables and certain object classes. Poisson regression. Algorithm that will allow us to see how several variables affect the number of times an event occurs. Central concepts in data science (overfitting vs underfitting, cross validation, variable preparation, etc). Any questions? Remember that we have a 30-day full money back guarantee. No risk for you. That's how convinced we are that you will love the course. Who this course is for Students interested in landing a job in the field of Data Science / Machine Learning. Professionals who want to apply predictive modelling to solve their hardest business problems. Machine learning practitioners who want to develop a deep understanding of how their algorithms work. Homepage https://www.udemy.com/course/data-science-ml-python/ Download ( Rapidgator ) https://rapidgator.net/file/01a8b1154d230317bdca994a22bd255a/sjahl.Data.Science.and.Machine.Learning.in.Python.Linear.models.rar.html [b]Download (Uploadgig)[/b] https://uploadgig.com/file/download/55646c0185189942/sjahl.Data.Science.and.Machine.Learning.in.Python.Linear.models.rar Download ( NitroFlare ) https://nitroflare.com/view/45740AF6C97AE82/sjahl.Data.Science.and.Machine.Learning.in.Python.Linear.models.rar Links are Interchangeable - No Password - Single Extraction
  25. Last updated 5/2020 MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz Language: English | Size: 1.24 GB | Duration: 3h 40m Learn Mysql by creating an e-commerce project database and creating 16 complex queries What you'll learn You will how to work with mysql databases from scratch You will learn how to use structured query language for creating tables, columns and keys You will learn how to design a medium sized ecommerce database You will learn how to create different types of relationships You will learn how to create and execute 16 complex queries for extracting complex data Requirements A computer or laptop Description Purpose of this course is to teach you how to use Mysql database management system. This course is created for complete beginner developers but as you progress you will become familiar with complicated matters, increase your experience and automatically enhance your level of expertise and become proficient in using Mysql and dealing with large databases. This course is made up of three sections.In section one: You will become familiar with Mysql database and get a simple and functional definition of database. You will learn how to set up environment to start work with Mysql You will create first database and table You will learn how to analyze structure of created table You will add unique key and columns to database table You will learn how to retrieve simple data form database table You will learn how to delete data from database table You will learn how to use simple and complex update command to update your tables You will learn concept of foreign key and how to establish connection between tables You will learn how to join tables and get more complex data You will learn about views and how to use them as sub queries in complex queriesIn section two: You will become familiar with a medium sized e-commerce application database You will learn different relationships which can be created between database tables You will create e-commerce database tables and execute simple queries on themIn section three: You will prepare your e-commerce database with massive data You will learn and execute 16 different and complex queries on database tables Overview Section 1: Fundamentals Lecture 1 Introduction & Installation Lecture 2 Create first database Lecture 3 Create first table Lecture 4 Analyse users table Lecture 5 Add unique key and more columns to users table Lecture 6 Retrieve data from users table with select command Lecture 7 Learn how to delete users Lecture 8 Learn simple and advanced ways of updating tables Lecture 9 Learn foreign key and how to connect tables Lecture 10 Learn how to join tables and get more complex data Lecture 11 Learn how to use views for more complex queries Section 2: Creating ecommerce database tables and relationships Lecture 12 Create ecommerce database and countries table Lecture 13 Create users table Lecture 14 Learn one to many relationship Lecture 15 Create categories table Lecture 16 Create products table Lecture 17 Create product_categories table Lecture 18 Learn many to many relationship Lecture 19 Create ratings table Lecture 20 Create orders and order_items tables Lecture 21 Create profiles table and learn one to one relationship Section 3: Complex queries Lecture 22 Prepare database with massive data Lecture 23 Get total number of users for each country Lecture 24 Get total number of users and total amount of orders for each country Lecture 25 Get total number and total amount of orders for each user Lecture 26 Get total quantity of ordered products for each user Lecture 27 Get each user ordered products with total sold count and total amount of pur... Lecture 28 Get each user with ordered categories along with total sold count and total a... Lecture 29 Get total number of products for each category Lecture 30 Get total number and total amount of orders for each country Lecture 31 Get each user's ratings count, ratings total and ratings average Lecture 32 Get ratings count, ratings total and ratings average given to each product Lecture 33 Get total number and total amount of orders for each month Lecture 34 Get ten most popular products Lecture 35 Get most popular product for each month Lecture 36 Get ten best seller products Lecture 37 Get best seller product for each month Lecture 38 Get best order of each user Those who want learn about databases with no prior experience,Those who want to learn ecommerce based database structure,Those who are familiar with mysql but want to take their knowledge to higher levels,Those who have basic sql experience but want to learn advanced queries,Beginner and intermidiate developers Homepage https://www.udemy.com/course/complete-mysql-tutorial-learning-16-complex-queries/ Download ( Rapidgator ) https://rapidgator.net/file/13989f9b73daeda4bb4b406c39cae267/vmyic.Complete.Mysql.Tutorial..Learning.16.Complex.Queries.part2.rar.html https://rapidgator.net/file/13db2d70a4b6131a8aa0b234d4db26b8/vmyic.Complete.Mysql.Tutorial..Learning.16.Complex.Queries.part1.rar.html [b]Download (Uploadgig)[/b] https://uploadgig.com/file/download/3deC4A88d5C0f7bf/vmyic.Complete.Mysql.Tutorial..Learning.16.Complex.Queries.part2.rar https://uploadgig.com/file/download/d9a2790c495980B7/vmyic.Complete.Mysql.Tutorial..Learning.16.Complex.Queries.part1.rar Download ( NitroFlare ) https://nitroflare.com/view/417AE0C8DEB8FB4/vmyic.Complete.Mysql.Tutorial..Learning.16.Complex.Queries.part2.rar https://nitroflare.com/view/592A8DD0B82B864/vmyic.Complete.Mysql.Tutorial..Learning.16.Complex.Queries.part1.rar Links are Interchangeable - No Password - Single Extraction
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