oaxino Posted September 11, 2024 Report Share Posted September 11, 2024 Numpy Programming Mastery: Learn Python For Data AnalysisPublished 9/2024MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHzLanguage: English | Size: 571.51 MB | Duration: 2h 30mMaster NumPy for Data Analysis: Learn Python Techniques for Efficient Data Manipulation and Complex ComputationsWhat you'll learnUnderstanding Arrays and MatricesCreating NumPy ArraysIndexing and Slicing ArraysJoining and Splitting ArraysStatistical OperationsBroadcasting and VectorizationLoading Data from FilesHandling Missing DataWorking with Structured ArraysImplementing Random Number GenerationAdvanced Indexing TechniquesPerformance Considerations in NumPyMemory Management in NumPyData Analysis with NumPyScientific Computing with NumPyMachine Learning with NumPyRequirementsNo Prior Knowledge is Required.DescriptionUnlock the power of data analysis with our comprehensive course, NumPy Programming Mastery: Learn Python for Data Analysis. Designed for both beginners and experienced programmers, this course provides an in-depth exploration of NumPy, the essential library for numerical computing in Python.What You'll Learn:Begin with the basics, including array creation, data types, and basic operations. Build a solid foundation in how NumPy handles large datasets with high efficiency.Dive deeper into complex array operations such as reshaping, slicing, and broadcasting. Learn how to perform sophisticated data manipulations and transformations with ease.Explore NumPy's extensive suite of mathematical functions for linear algebra, statistical analysis, and random number generation. Gain practical skills in performing high-level calculations and data analysis.Understand how to seamlessly integrate NumPy with other Python libraries like Pandas and Matplotlib to enhance your data analysis workflow.Apply your knowledge through hands-on projects and real-world case studies. Work on practical examples that simulate real data analysis scenarios, reinforcing your learning and boosting your confidence.Course Features:Engaging video tutorials and coding exercises designed to reinforce key concepts.Real-life projects that provide practical experience and showcase your skills.Learn from experienced instructors with a deep understanding of data analysis and NumPy.Whether you're looking to enhance your data analysis skills or embark on a new career in data science, NumPy Programming Mastery offers the tools and expertise you need to succeed. Enroll today and start your journey toward mastering Python for data analysis!OverviewSection 1: Section 1: Getting Started with NumPyLecture 1 Understanding Arrays and MatricesLecture 2 Creating NumPy ArraysLecture 3 Basic Array OperationsSection 2: Section 2: NumPy Array ManipulationLecture 4 Indexing and Slicing ArraysLecture 5 Reshaping and Flattening ArraysLecture 6 Joining and Splitting ArraysLecture 7 Copying and Viewing ArraysSection 3: Section 3: NumPy Mathematical OperationsLecture 8 Basic Mathematical FunctionsLecture 9 Statistical OperationsLecture 10 Linear Algebra with NumPyLecture 11 Broadcasting and VectorizationSection 4: Section 4: Working with Data in NumPyLecture 12 Loading Data from FilesLecture 13 Saving Data to FilesLecture 14 Handling Missing DataLecture 15 Working with Structured ArraysSection 5: Section 5: Advanced NumPy TechniquesLecture 16 Using NumPy for Image ProcessingLecture 17 Implementing Random Number GenerationLecture 18 Advanced Indexing TechniquesLecture 19 Optimization with NumPySection 6: Section 6: Performance and OptimizationLecture 20 Performance Considerations in NumPyLecture 21 Using Cython to Speed Up NumPyLecture 22 Integrating NumPy with Other LibrariesAnyone interested to learning NumPy Programming Mastery Python for Data AnalysisScreenshotsrapidgator.net:https://rapidgator.net/file/8004f124be8abf3e22ea10f53964e88a/bhbnm.Numpy.Programming.Mastery.Learn.Python.For.Data.Analysis.rar.htmlnitroflare.com:https://nitroflare.com/view/DEB3F4909A6D19A/bhbnm.Numpy.Programming.Mastery.Learn.Python.For.Data.Analysis.rar Link to comment Share on other sites More sharing options...
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