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Free Download Udemy - Fundamentals Of Medical Devices Published: 12/2024 MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz Language: English | Size: 2.24 GB | Duration: 3h 30m Introduction to Medical Devices &IVDs What you'll learn Different definitions of Medical Devices and In-Vitro Diagnostics IVDs Classifications of Medical Devices and In-Vitro Diagnostics IVDs Regulations of Medical Devices and IVDs Quality Management System Requirements This course is for beginners in regulatory affairs of medical devices and who wish to know the basics behind the medical devices Scientific background is required but not mandatory Description This course offers a comprehensive introduction to the regulatory landscape for medical devices. It covers essential topics such as device classification, regulatory frameworks, clinical evaluation, quality management systems, and post-market surveillance. Participants will gain practical insights into the key regulatory Requirements and processes necessary for compliance in major global markets.Who Should Attend?This course is ideal for:- New professionals in the medical device industry.- Regulatory affairs professionals transitioning from other industries.- Quality assurance and compliance personnel.- R&D engineers and project managers.- Healthcare professionals interested in regulatory aspects of medical devices.- Anyone seeking a foundational understanding of medical device regulations.Learning Outcomes:By the end of this course, participants will be able to:1. Understand the regulatory classification of medical devices.2. Navigate key global regulatory frameworks, including EU MDR and FDA regulations.3. Develop and maintain technical documentation and quality management systems.4. Prepare for regulatory submissions and market access.Outlines:1. Introduction to Medical Devices- Definition and examples- Device vs. pharmaceuticals2. Regulatory Frameworks- Overview of global regulations- Key regulatory authorities3. Device Classification- Classification criteria and examples- Risk-based classification4. Conformity Assessment and CE Marking- Notified Bodies and their roles- Steps to obtain CE marking5. Technical Documentation- Essential components- Preparing a technical file6. Quality Management Systems (QMS)- ISO 13485 Overview- QMS implementation7. Regulatory Submissions and Approvals- Submission processes for major markets- Interactions with regulatory authorities Overview Section 1: Introduction Lecture 1 WHO Definition of Medical Devices Lecture 2 WHO Definition of In-Vitro Diagnostics IVDs Lecture 3 FDA Definition Lecture 4 EU definitions Lecture 5 Intended purpose & Notified Bodies Lecture 6 Is my product a medical device? Section 2: Classifications of Medical Devices Lecture 7 Importance of Classification & WHO Lecture 8 EU classification 1 Lecture 9 EU Classification 2 Lecture 10 Examples Lecture 11 FDA Classification Lecture 12 FDA Class II submissions Lecture 13 Classification in KSA, UAE, and Egypt Section 3: Regulatory Requirements Lecture 14 WHO Regulations Lecture 15 FDA Regulations Lecture 16 EMA regulations Lecture 17 Saudi FDA Regulations Lecture 18 UAE Regulations Lecture 19 Egypt Regulations Section 4: In-Vitro Diagnostics (IVDs) Lecture 20 In-Vitro Diagnostics (IVDs) Section 5: Unique Device Identifier Lecture 21 Unique Device Identifier Section 6: Quality Management System Lecture 22 Quality Management System Fresh graduates from scientific field,Regulatory affairs specialists,medical devices engineers Homepage: https://www.udemy.com/course/fundamentals-of-medical-devices/ DOWNLOAD NOW: Udemy - Fundamentals Of Medical Devices Download ( Rapidgator ) https://rg.to/file/46b21a0287be81bb64cb6f4d7fddca07/dukyh.Udemy..Fundamentals.Of.Medical.Devices.part3.rar.html https://rg.to/file/e4e79dcbbecae6567e69c1979990ac47/dukyh.Udemy..Fundamentals.Of.Medical.Devices.part1.rar.html https://rg.to/file/ee615659545aac5fdf9fb279315a2d65/dukyh.Udemy..Fundamentals.Of.Medical.Devices.part2.rar.html Fikper https://fikper.com/LQYEUsxF2u/dukyh.Udemy..Fundamentals.Of.Medical.Devices.part3.rar.html https://fikper.com/gU94UeDcn2/dukyh.Udemy..Fundamentals.Of.Medical.Devices.part2.rar.html https://fikper.com/rgoiBzCzwJ/dukyh.Udemy..Fundamentals.Of.Medical.Devices.part1.rar.html No Password - Links are Interchangeable

Free Download Udemy - Fundamentals Of Investigative Interviewing Published: 12/2024 MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz Language: English | Size: 3.53 GB | Duration: 2h 27m How to Gather Information from (Almost) Anyone What you'll learn Learn how to question people effectively Understand how to build rapport with interviewees Learn how to plan effectively for interviews Understand how to gather and challenge an interviewee's account Requirements No previous experience needed, although some investigative experience would be an asset Description Throughout the course Dr. Eastwood presents evidence-based concepts related to effective interviewing that are rooted in psychological science. This includes topics such as: core attributes of every successful interviewer, how to plan for an interview, creating an atmosphere that will ensure that the interviewee will want to talk, systematic questioning processes for both cooperative and uncooperative interviewees, how to close an interview in a professional manner, and evaluating performance once the interview is completed.Along with the theoretical concepts, Detective Mitton discusses a variety of applications, illustrations, and personal anecdotes from his 30 years of experience in conducting high-level interviews within a law enforcement context. As with all of our content, this combination of science and experience ensures the content is both research-based and practically relevant.The course consists of six sections: Introduction, Planning, Opening, Account - Cooperative, Account - Uncooperative, and Closing & Evaluation. Each section consists of a brief course Overview, a video lecture, accompanying ppt slides, the corresponding chapter from our written Interviewing Manual, supplementary videos illustrating the section content, and a short multiple-choice question quiz.This course was designed for investigators of all types, including law enforcement, HR professionals, social workers, loss prevention, medical staff, and beyond. While the examples used often include cases of a criminal nature, the concepts covered in the course can be applied to any questioning context.The goal of the course is to make trainees more skilled and efficient at extracting information from other people, and so anyone whose job involves talking to, and gathering information from, someone else will benefit from this course. The course is designed primarily for building a solid evidence-based foundation of core interviewing concepts, and so any investigator looking to create or supplement their knowledge and skills in this area will find this course particularly helpful. Overview Section 1: Section 1 - Introduction Lecture 1 Section 1: Introduction Lecture 2 Section 1: Illustrative Example Section 2: Section 2 - Planning Lecture 3 Section 2: Pre-Interview Planning Lecture 4 Section 2: Illustrative Example Section 3: Section 3 - Opening Lecture 5 Section 3 - Opening Phase Lecture 6 Section 3: Illustrative Example Section 4: Section 4 - Account (Cooperative) Lecture 7 Section 4 - Account (Cooperative) Lecture 8 Section 4: Illustrative Example Section 5: Section 5 - Account (Uncooperative) Lecture 9 Section 5 - Account (Uncooperative) Lecture 10 Section 5: Illustrative Example Section 6: Section 6 - Closure & Evaluation Lecture 11 Section 6 - Closure & Evaluation Lecture 12 Section 6: Illustrative Example Investigators of all types wanting to improve their interviewing skills. This includes law enforcement, HR professionals, lawyers, social workers, and more. Homepage: https://www.udemy.com/course/fundamentals-of-investigative-interviewing/ DOWNLOAD NOW: Udemy - Fundamentals Of Investigative Interviewing Download ( Rapidgator ) https://rg.to/file/1b64d42714cbdaa8a532799231b93d11/trlsb.Udemy..Fundamentals.Of.Investigative.Interviewing.part4.rar.html https://rg.to/file/9621bce82dc4be39be9e88e4d3871666/trlsb.Udemy..Fundamentals.Of.Investigative.Interviewing.part1.rar.html https://rg.to/file/a8c4e2bdc277e59e3488b2e4983a375c/trlsb.Udemy..Fundamentals.Of.Investigative.Interviewing.part3.rar.html https://rg.to/file/fd39c8b56a2157572daa90958c49af42/trlsb.Udemy..Fundamentals.Of.Investigative.Interviewing.part2.rar.html Fikper https://fikper.com/HKoCXxBvGp/trlsb.Udemy..Fundamentals.Of.Investigative.Interviewing.part4.rar.html https://fikper.com/L5AqQjGMTG/trlsb.Udemy..Fundamentals.Of.Investigative.Interviewing.part3.rar.html https://fikper.com/fluxjQP1t6/trlsb.Udemy..Fundamentals.Of.Investigative.Interviewing.part1.rar.html https://fikper.com/pc81lyeJFw/trlsb.Udemy..Fundamentals.Of.Investigative.Interviewing.part2.rar.html No Password - Links are Interchangeable

Free Download Udemy - Fundamentals Of Generative AI Published: 12/2024 MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz Language: English | Size: 986.56 MB | Duration: 1h 19m Master all Importance basics of Generative AI with examples and Learn more about generative What you'll learn Learn how to use Generative AI in Learning and Development the skills Learn How to generate Automated Content with Generative AI Master some vital Generative and ChatGPT for learning and development Learn how to use ChatGPT in learning and development Requirements You must have a working computer Description Generative AI is a branch of artificial intelligence that focuses on creating models capable of generating new, human-like content such as text, images, music, or code. It is underpinned by deep learning and neural networks, which allow machines to learn patterns from vast datasets and produce novel outputs. Unlike traditional AI systems designed to perform specific tasks or make decisions based on predefined rules, generative AI models aim to simulate creativity by creating original and contextually relevant content.Generative AI has numerous applications, spanning multiple industries. In natural language processing, it powers chatbots, virtual assistants, and automated content creation tools. In visual domains, it is used for designing graphics, generating realistic images, and enhancing creative workflows. In healthcare, generative AI supports drug discovery, simulates medical scenarios, and aids in diagnostic imaging. It also plays a role in personalized education and entertainment, offering tailored solutions to users. For instance, a text-based model like GPT is trained on vast corpora of written material to learn grammar, syntax, and context. Through this training, the model identifies patterns and constructs probabilistic representations, allowing it to produce outputs that align with the training data's style and structure.Generative AI blends computational power and creativity, offering tools that augment human capabilities. As it evolves, its fundamental principles-data, algorithms, and training-will continue to drive its transformative impact, shaping the future of technology and society. Overview Section 1: Introduction Lecture 1 Introduction Section 2: Generative AI Basics Lecture 2 What is Generative AI Lecture 3 Generative AI NLP Section 3: Data ingestion in Generative AI Lecture 4 Data Ingestion and Preperation in Generative AI Lecture 5 Generative AI Various Commands Section 4: Interface in Generative AI Lecture 6 Interface of Jupyter in Generative AI Lecture 7 Version Control System in Generative AI It is for those who want to learn with Generative AI and ChatGPT Homepage: https://www.udemy.com/course/fundamentals-of-generative-ai/ DOWNLOAD NOW: Udemy - Fundamentals Of Generative AI Download ( Rapidgator ) https://rg.to/file/8addbff562e85e62f0600afb8662ad2b/ivvef.Udemy..Fundamentals.Of.Generative.AI.rar.html Fikper https://fikper.com/z9bEzFkJ0Q/ivvef.Udemy..Fundamentals.Of.Generative.AI.rar.html No Password - Links are Interchangeable

Free Download Udemy - Full Cypress Guide From Beginner To Advanced Published: 12/2024 MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz Language: English | Size: 6.94 GB | Duration: 10h 39m Learn Cypress from inside to create your own non-flaky automation solution which will definitely catch some bugs! What you'll learn Gain manual skills needed at work as an Automation QA Define test cases which should be automated Create Cypress automation project from scratch Practical skills of writing integration and end-to-end-tests Correct usage of Cypress commands, tasks, interceptors and 3rd party libraries Generate test report with given test results Requirements Basic programming skills Experience in manual testing Description Hello everyone and welcome to my course. Here I wanted to share some thoughts of why I decided to create it.First of all I believe no matter of what your skills or level you are, you will always create some tests, but only the easy ones or the one you learnt from another courses on watched in tutorials. But my goal is not to teach to write tests but to teach you how to use the Cypress tool, how it works. Because only in that case no matter what project you will be working on, knowing about how Cypress works from the inside, what are advantages and limitation, you will be able to think of new unique solutions, types of tests needed for that particular project. That will define your professionalism, skill to know how to use the tool with the knowledge but not just the ability to write tests. Because we need quality over quantity, right?? So those tests are written thoughtfully and carefully, which won't fail after some time and will actually be stable and catch bugs sprint after sprint. Hope you will share my goal and I will see you in my course. I wish you a happy learning! Overview Section 1: Get started with Cypress Lecture 1 What is Cypress, why and what kind of tests can be written Lecture 2 How to install and launch Cypress Lecture 3 Cypress config Lecture 4 Cypress support folder Lecture 5 Cypress first test Section 2: Cypress basics Lecture 6 Cypress basic commands and assertions Lecture 7 Query commands Lecture 8 Assertion commands Lecture 9 Action commands Lecture 10 Other commands Lecture 11 Summarize knowledge about Cypress basic commands Lecture 12 Cypress retry-ability Lecture 13 Cypress chain managment Lecture 14 Cypress custom commands Lecture 15 Cypress custom queries Lecture 16 Cypress from the inside summary (article) Lecture 17 Interceptors, fixtures and requests Lecture 18 Intercept - spy on the request Lecture 19 Intercept - mock a request Lecture 20 Intercept with fixture Lecture 21 Cypress requests Lecture 22 Summarize knowledge about interceptors and requests Lecture 23 Hooks Lecture 24 Practical lesson Section 3: Advanced Cypress Lecture 25 Tasks Lecture 26 Authentication (session, cookies, local storage, etc.) Lecture 27 Cypress 'on' events Lecture 28 How to test unsupported features in Cypress Section 4: Page object Lecture 29 What is a PageObject pattern? 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Free Download Neural Networks & Deep Learning For Business Transformation Published: 12/2024 MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz Language: English | Size: 5.82 GB | Duration: 5h 18m Master Deep Learning: Neural Networks, NLP, GANs, Image Recognition, and Business Applications What you'll learn Explain the basic structure and function of artificial neural networks. Describe the process and significance of neuron activation functions. Apply feedforward and backpropagation techniques to simple neural network models. Implement gradient descent to optimize neural network performance. Evaluate the application of neural networks in resolving real-world business challenges. Differentiate between deep learning and traditional machine learning in terms of capabilities and applications. Construct deep neural network architectures for complex problem-solving. Utilize convolutional neural networks (CNNs) for image data processing and analysis. Develop recurrent neural networks (RNNs) for sequence data prediction and classification. Analyze deep learning's impact across various industries through case studies. Apply regularization and dropout techniques to prevent overfitting in neural networks. Execute hyperparameter tuning to enhance neural network models. Leverage transfer learning to improve model efficiency with pre-trained networks. Tailor neural network models for specific business scenarios through fine-tuning. Process and prepare image data for machine learning applications. Design object detection systems using CNNs for real-time applications. Conduct image classification tasks using deep learning techniques. Preprocess text data for natural language processing (NLP) applications. Implement long short-term memory (LSTM) networks for sentiment analysis. Generate realistic images using generative adversarial networks (GANs) for creative purposes. Requirements There are no Requirements or pre-requisites for this course, but the items listed below are a guide to useful background knowledge which will increase the value and benefits of this course. Basic understanding of programming concepts (preferably in Python). Fundamental knowledge of mathematics, especially algebra and calculus. Familiarity with basic statistics and probability. Description Welcome to our comprehensive course on "Deep Learning and Neural Networks for Business," where we dive into the cutting-edge world of artificial intelligence and its practical applications within various industries. Are you ready to unlock the power of deep learning to enhance business operations, improve decision-making processes, and drive innovation in the digital age?In this course, we share our expertise and knowledge gathered from years of experience in the field of artificial intelligence and machine learning. Our team is passionate about empowering individuals like you to harness the potential of neural networks and deep learning algorithms to optimize business strategies and make data-driven decisions.The course is designed to cater to a wide range of learners, from beginners aspiring to enter the world of deep learning to seasoned professionals seeking to enhance their skills and stay abreast of the latest advancements in AI technology. Throughout the course, we guide you through a structured learning journey, starting with the fundamentals of neural networks and gradually progressing to more advanced topics such as deep learning architectures, natural language processing, and reinforcement learning. One of the unique aspects of our course is the emphasis on practical applications and real-world case studies. You will have the opportunity to work on hands-on projects, including image recognition, sentiment analysis, time series forecasting, and customer segmentation, allowing you to apply theoretical knowledge in a practical setting. By the end of the course, you will have developed a diverse skill set in deep learning and neural networks, ready to tackle complex business challenges and drive innovation within your organization.Our course stands out from the rest by providing a holistic approach to deep learning and neural networks, combining theoretical foundations with hands-on experience to ensure a comprehensive understanding of the subject matter. We prioritize practical relevance, ensuring that the skills you acquire are directly applicable to real-world scenarios, making you a valuable asset in the ever-evolving digital landscape.Join us on this transformative learning journey and embark on a path towards mastering deep learning technologies for business optimization and strategic decision-making. Whether you are a business professional looking to leverage AI for competitive advantage or a tech enthusiast seeking to delve into the world of neural networks, this course is your gateway to unlocking the full potential of artificial intelligence in the business realm.Enroll now and embark on a journey that will not only enhance your skill set but also position you at the forefront of the AI revolution, shaping the future of business with deep learning insights and innovative solutions. The possibilities are limitless, and the opportunities are boundless. Let's embark on this transformative journey together, and unleash the power of deep learning for business success. Overview Section 1: Fundamentals of Neural Networks Lecture 1 Introduction to Artificial Neural Networks Lecture 2 Download The *Amazing* +100 Page Workbook For this Course Lecture 3 Get This Course In Audio Format: Download All Audio Files From This Lecture Lecture 4 Introduce Yourself And Tell Us Your Awesome Goals With This Course Lecture 5 Neuron Structure and Activation Functions Lecture 6 Feedforward and Backpropagation Lecture 7 Gradient Descent in NNs Lecture 8 Applications of Neural Networks in Business Lecture 9 Let's Celebrate Your Progress In This Course: 25% > 50% > 75% > 100% Section 2: Understanding Deep Learning Lecture 10 Deep Learning vs. Traditional Machine Learning Lecture 11 Deep Neural Networks Architecture Lecture 12 Convolutional Neural Networks Lecture 13 Recurrent Neural Networks Lecture 14 Deep Learning Applications in Industry Section 3: Neural Network Training Techniques Lecture 15 Optimizing Neural Network Performance Lecture 16 Regularization and Dropout Lecture 17 Hyperparameter Tuning Lecture 18 Transfer Learning Lecture 19 Fine-Tuning Neural Networks for Business Scenarios Section 4: Deep Learning for Image Recognition Lecture 20 Image Data Preprocessing Lecture 21 Convolutional Neural Networks for Images Lecture 22 Object Detection with CNNs Lecture 23 Deep Learning for Image Classification Lecture 24 Real-Life Image Recognition Case Studies Section 5: Natural Language Processing with Neural Networks Lecture 25 Text Preprocessing for NLP Lecture 26 Recurrent Neural Networks for Text Data Lecture 27 Word Embeddings and LSTM Lecture 28 Sentiment Analysis using RNNs Lecture 29 NLP Applications in Business Communication Lecture 30 You've Achieved 25% >> Let's Celebrate Your Progress And Keep Going To 50% Section 6: Generative Adversarial Networks (GANs) Lecture 31 Introduction to GANs Lecture 32 GAN Architecture and Training Process Lecture 33 Applications of GANs in Image Generation Lecture 34 Challenges and Ethical Considerations of GANs Lecture 35 Examples of GANs in Creative Industries Section 7: Time Series Forecasting with RNNs Lecture 36 Introduction to Time Series Data Analysis Lecture 37 Recurrent Neural Networks for Time Series Lecture 38 Long Short-Term Memory Networks Lecture 39 Predictive Analytics with RNNs Lecture 40 Time Series Forecasting in Business Contexts Section 8: Anomaly Detection with Autoencoders Lecture 41 Understanding Anomalies in Data Lecture 42 Autoencoder Architecture Lecture 43 Denoising Autoencoders Lecture 44 Applications of Anomaly Detection in Fraud Lecture 45 Real-Time Anomaly Detection Use Cases Section 9: Reinforcement Learning Fundamentals Lecture 46 Reinforcement Learning Basics Lecture 47 Q-Learning and Markov Decision Processes Lecture 48 Deep Q Networks (DQN) Lecture 49 Policy Gradient Methods Lecture 50 Reinforcement Learning in Game Theory Section 10: Neural Networks for Customer Segmentation Lecture 51 Segmentation Methods in Marketing Lecture 52 Neural Network Clustering Techniques Lecture 53 Targeted Marketing Campaigns Lecture 54 Customer Lifetime Value Prediction Lecture 55 Case Studies on Neural Segmentation in Business Lecture 56 You've Achieved 50% >> Let's Celebrate Your Progress And Keep Going To 75% Section 11: Test your knowledge now to achieve your goals! Section 12: Sentiment Analysis in Social Media Lecture 57 Social Media Data and Sentiment Analysis Lecture 58 Deep Learning for Sentiment Detection Lecture 59 Engagement Prediction with Sentiment Analysis Lecture 60 Brand Reputation Monitoring Lecture 61 Sentiment Analysis in Influencer Marketing Section 13: Deep Learning for Business Optimization Lecture 62 Optimizing Business Processes with DL Lecture 63 Automating Decision-Making Lecture 64 Dynamic Pricing Strategies Lecture 65 Supply Chain Optimization Lecture 66 DL in Inventory Management Section 14: Neural Networks for Financial Forecasting Lecture 67 Predictive Analytics in Finance Lecture 68 Stock Price Prediction with NNs Lecture 69 Risk Management in Banking Lecture 70 Credit Scoring using Neural Networks Lecture 71 Applications of NNs in Financial Sector Section 15: Fraud Detection using Deep Learning Lecture 72 Fraud Detection Techniques Lecture 73 Deep Learning Models for Fraud Lecture 74 Behavior-based Fraud Detection Lecture 75 Anti-Money Laundering with DL Lecture 76 Case Studies in Fraud Detection Section 16: Business Strategy with Deep Learning Insights Lecture 77 DL for Competitive Analysis Lecture 78 Predictive Marketing Strategies Lecture 79 Market Segmentation with NNs Lecture 80 Strategic Decision Support Systems Lecture 81 Deep Learning for Disruption Forecasting Lecture 82 You've Achieved 75% >> Let's Celebrate Your Progress And Keep Going To 100% Section 17: Neural Networks in Healthcare Management Lecture 83 Medical Image Analysis with NNs Lecture 84 DL for Disease Diagnosis Lecture 85 Healthcare Data Security with Deep Learning Lecture 86 Treatment Outcome Prediction Lecture 87 Real-World Healthcare Applications of NNs Section 18: Deep Learning for HR Management Lecture 88 Talent Recruitment with Neural Networks Lecture 89 Employee Performance Prediction Lecture 90 Retention Strategies using Deep Learning Lecture 91 Skills Gap Analysis Lecture 92 HR Decision Support Systems Section 19: Neural Networks for Supply Chain Optimization Lecture 93 Forecasting Demand in Supply Chains Lecture 94 Inventory Management with NNs Lecture 95 Predictive Maintenance in Logistics Lecture 96 Route Optimization using Neural Networks Lecture 97 Applications of NNs in Supply Chain Efficiency Section 20: Customer Personalization with Neural Networks Lecture 98 Personalized Recommendations Lecture 99 Segment-Specific Campaigns Lecture 100 Customer Lifetime Value Prediction Lecture 101 Neural Networks in Customer Retention Lecture 102 Case Studies on Personalization Success Section 21: Implementing Deep Learning Strategies Lecture 103 Integration of Neural Networks in Business Lecture 104 Data Privacy and Ethical Considerations Lecture 105 Change Management in DL Adoption Lecture 106 Organizational Culture Shifts Lecture 107 Future Trends and Opportunities in DL Implementation Lecture 108 You've Achieved 100% >> Let's Celebrate! Remember To Share Your Certificate!! Section 22: Test your knowledge now to achieve your goals! Section 23: Your Assignment: Write down goals to improve your life and achieve your goals!! Data Scientists looking to specialize in deep learning.,Business Analysts interested in leveraging neural networks for predictive analytics.,Software Developers aiming to build intelligent applications with neural networks.,Marketing Professionals seeking to apply deep learning for customer segmentation and personalized marketing campaigns.,HR Managers wanting to understand and implement deep learning strategies for talent recruitment and employee performance prediction.,Healthcare Professionals focusing on medical image analysis and disease diagnosis through neural networks. 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