[FreeCourseSite.com] Udemy - Complete Python Data Science, Deep Learning, R Programming

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[FreeCourseSite.com] Udemy - Complete Python Data Science, Deep Learning, R Programming

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收录时间：2023-12-21
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文件列表

  • 27. Data Transformation in R/3. Filtering Rows with Filter Function in R programming.mp4 177.9 MB
  • 18. Projects Python projects, Data science projects, machine learning/2. Project - 2.mp4 177.5 MB
  • 11. Geoplotlib/3.1 world_cities_pop.csv 164.3 MB
  • 12. Data Science Hands-On Projects/6. Answer for Housing and Property Sales Project.mp4 162.6 MB
  • 12. Data Science Hands-On Projects/8. Answers for English Premier League Project.mp4 161.0 MB
  • 13. Machine Learning/15. Choosing the right algorithm and model in deep learning.mp4 156.1 MB
  • 27. Data Transformation in R/6. Grouped Summaries with Summarize Function in R.mp4 155.8 MB
  • 12. Data Science Hands-On Projects/4. Bike Sharing Project Answers.mp4 154.4 MB
  • 25. Data Frames/3. Manipulating Values in DF.mp4 152.3 MB
  • 20. Data Management in R/3. Graphs and Charts in Python data science.mp4 146.6 MB
  • 26. Factors in R/2. Manipulating Categorical Data with Forcats in R.mp4 139.2 MB
  • 27. Data Transformation in R/4. Arranging Rows with Arrange Function in R.mp4 135.6 MB
  • 9. Matplotlib/8. Basic Plots in Matplotlib I.mp4 109.5 MB
  • 8. Data Frame with Pandas/9. Combining Data Frames in Pandas.mp4 108.6 MB
  • 18. Projects Python projects, Data science projects, machine learning/1. Project - 1.mp4 106.5 MB
  • 10. Seaborn/5. Basic Plots in Seaborn.mp4 97.3 MB
  • 12. Data Science Hands-On Projects/2. Titanic Project Answers in python projects.mp4 93.3 MB
  • 13. Machine Learning/12. Unsupervised Machine Learning Methods.mp4 92.2 MB
  • 17. Transfer Learning/1. What is Transfer Learning.mp4 89.5 MB
  • 8. Data Frame with Pandas/10. Combining Data Frames Part – II.mp4 88.3 MB
  • 13. Machine Learning/16. Training and testing the model.mp4 88.1 MB
  • 25. Data Frames/5. Tibbles in R.mp4 87.8 MB
  • 18. Projects Python projects, Data science projects, machine learning/3. Project - 3.mp4 86.4 MB
  • 8. Data Frame with Pandas/1. Data Frame Attributes and Methods.mp4 83.6 MB
  • 14. Artificial Neural Network/3. Creating a Simple ANN in Artificial intelligence.mp4 83.4 MB
  • 8. Data Frame with Pandas/6. Missing Data and Data Munging in Pandas.mp4 83.2 MB
  • 11. Geoplotlib/3. Example - 2.mp4 80.0 MB
  • 27. Data Transformation in R/1. Introduction to Data Transformation.mp4 79.9 MB
  • 7. Pandas Using Pandas for Data Manipulation/2. Series and Features.mp4 77.9 MB
  • 6. Using Numpy for Data Manipulation/5. Numpy Exercises.mp4 77.8 MB
  • 15. Convolutional Neural Network (CNN)/1. What is CNN.mp4 75.9 MB
  • 18. Projects Python projects, Data science projects, machine learning/4. Project - 4.mp4 75.8 MB
  • 25. Data Frames/1. Introduction to Data Frames.mp4 74.4 MB
  • 8. Data Frame with Pandas/11. Work with Dataset Files in Pandas.mp4 74.2 MB
  • 13. Machine Learning/11. Supervised Machine Learning Methods - 4.mp4 73.7 MB
  • 8. Data Frame with Pandas/8. How We Deal with Missing Data.mp4 72.6 MB
  • 23. Arrays in R/2. Subsections of an Array in r programming.mp4 71.8 MB
  • 3. Fundamentals of Python/5. Lists, Tuples, Dictionaries and Sets in Python.mp4 69.6 MB
  • 9. Matplotlib/4. Figure, Subplot and Axes in Matplotlib.mp4 68.8 MB
  • 27. Data Transformation in R/5. Adding New Variables with Mutate Function in R.mp4 66.2 MB
  • 14. Artificial Neural Network/8. What is TensorFlow.mp4 65.7 MB
  • 14. Artificial Neural Network/4. Tensor Operations in Artificial intelligence.mp4 65.1 MB
  • 27. Data Transformation in R/2. Select Columns with Select Function in R programming.mp4 63.5 MB
  • 24. Matrices in R programming/3. Calculating With Matrices in Python Data science.mp4 62.0 MB
  • 9. Matplotlib/5. Figure Customization in Matplotlib.mp4 61.9 MB
  • 4. Object Oriented Programming/5. Overriding and Overloading in OOP.mp4 61.7 MB
  • 8. Data Frame with Pandas/2. Data Frame Attributes and Methods Part – II.mp4 59.7 MB
  • 10. Seaborn/7. Regression Plots and Squarify in Seaborn.mp4 59.2 MB
  • 13. Machine Learning/10. Supervised Machine Learning Methods - 3.mp4 58.8 MB
  • 13. Machine Learning/9. Supervised Machine Learning Methods - 2.mp4 58.1 MB
  • 20. Data Management in R/2. Data Manipulation in R.mp4 57.6 MB
  • 2. Setting Up Python for Mac and Windows Python Data Science/2. Installing Anaconda for Mac, Python Data Science.mp4 55.6 MB
  • 8. Data Frame with Pandas/5. Groupby Operations in Pandas.mp4 55.2 MB
  • 9. Matplotlib/9. Basic Plots in Matplotlib II.mp4 54.0 MB
  • 10. Seaborn/3. Example in Seaborn.mp4 53.8 MB
  • 16. Recurrent Neural Network and LTSM/1. Understanding RNN and LSTM Networks.mp4 53.3 MB
  • 8. Data Frame with Pandas/4. Multi Index in Pandas.mp4 53.3 MB
  • 24. Matrices in R programming/1. Matrices in R programming.mp4 52.4 MB
  • 3. Fundamentals of Python/4. Loops in Python.mp4 51.5 MB
  • 24. Matrices in R programming/2. Naming Matrix Row and Columns in R programming.mp4 50.4 MB
  • 8. Data Frame with Pandas/3. Data Frame Attributes and Methods Part – III.mp4 50.4 MB
  • 6. Using Numpy for Data Manipulation/2. Array and Features in Numpy Python.mp4 50.2 MB
  • 11. Geoplotlib/4. Example - 3.mp4 50.1 MB
  • 3. Fundamentals of Python/10. Exercise Solution in Python.mp4 50.0 MB
  • 21. Examining and Managing Data Structures in R/7. Subsetting Vectors in R.mp4 48.4 MB
  • 13. Machine Learning/7. Machine Learning Methods.mp4 47.8 MB
  • 10. Seaborn/4. Color Palettes in Seaborn.mp4 47.7 MB
  • 22. Lists in R/1. Lists in R.mp4 45.4 MB
  • 14. Artificial Neural Network/7. Optimizers in Artificial intelligence.mp4 44.4 MB
  • 14. Artificial Neural Network/2. Anatomy of Neural Network in Artificial intelligence.mp4 44.3 MB
  • 21. Examining and Managing Data Structures in R/1. Vector Basics in R.mp4 44.0 MB
  • 25. Data Frames/4. Adding and Removing Variables in R Programming.mp4 43.5 MB
  • 3. Fundamentals of Python/1. Data Types in Python.mp4 43.1 MB
  • 10. Seaborn/6. Multi-Plots in Seaborn.mp4 42.9 MB
  • 13. Machine Learning/3. Turing Machine and Turing Test.mp4 42.9 MB
  • 8. Data Frame with Pandas/7. Missing Data and Data Munging Part II.mp4 42.8 MB
  • 3. Fundamentals of Python/6. Data Type Operators and Methods in Python.mp4 42.4 MB
  • 6. Using Numpy for Data Manipulation/4. Indexing and Slicing in Numpy Python.mp4 42.3 MB
  • 2. Setting Up Python for Mac and Windows Python Data Science/1. Installing Anaconda for Windows.mp4 42.1 MB
  • 10. Seaborn/2. Controlling Figure Aesthetics in Seaborn.mp4 41.1 MB
  • 20. Data Management in R/1. Getting Data into R.mp4 38.6 MB
  • 11. Geoplotlib/2. Example - 1.mp4 38.1 MB
  • 13. Machine Learning/5. Learning representations from data.mp4 36.6 MB
  • 3. Fundamentals of Python/3. Conditionals in Python.mp4 36.3 MB
  • 26. Factors in R/1. Introduction to Factors in R.mp4 36.3 MB
  • 21. Examining and Managing Data Structures in R/5. Vector Recycling and Iterations in R.mp4 36.2 MB
  • 21. Examining and Managing Data Structures in R/6. Naming Vectors in R.mp4 35.9 MB
  • 4. Object Oriented Programming/2. Constructor in Object Oriented Programming.mp4 35.5 MB
  • 4. Object Oriented Programming/4. Inheritance in Object Oriented Programming.mp4 34.2 MB
  • 11. Geoplotlib/1. What is Geoplotlib.mp4 33.8 MB
  • 21. Examining and Managing Data Structures in R/3. Converting Data Types of Atomic Vectors in R.mp4 33.7 MB
  • 13. Machine Learning/6. Workflow of Machine Learning.mp4 33.2 MB
  • 13. Machine Learning/8. Supervised Machine Learning Methods - 1.mp4 32.4 MB
  • 14. Artificial Neural Network/5. Tensor Operations 2.mp4 31.2 MB
  • 3. Fundamentals of Python/2. Operators in Python.mp4 31.1 MB
  • 23. Arrays in R/1. Arrays in r programming.mp4 29.4 MB
  • 25. Data Frames/2. Naming Variables and Observations in DF.mp4 28.9 MB
  • 6. Using Numpy for Data Manipulation/1. What is Numpy.mp4 28.0 MB
  • 9. Matplotlib/3. Pyplot – Pylab - Matplotlib.mp4 27.9 MB
  • 9. Matplotlib/2. Using Matplotlib.mp4 27.8 MB
  • 3. Fundamentals of Python/8. Functions in Python.mp4 27.3 MB
  • 13. Machine Learning/14. Data pre-processing in Deep learning.mp4 27.2 MB
  • 9. Matplotlib/6. Plot Customization in matplotlib.mp4 27.0 MB
  • 2. Setting Up Python for Mac and Windows Python Data Science/3. Let's Meet Jupyter Notebook for Windows.mp4 26.6 MB
  • 19. Environment Installation for R/1. Downloading and Installing R & R Studio.mp4 26.3 MB
  • 13. Machine Learning/17. Evaluation in deep learning.mp4 25.6 MB
  • 21. Examining and Managing Data Structures in R/2. Atomic Vector Types in R.mp4 25.2 MB
  • 13. Machine Learning/2. History of Machine Learning.mp4 25.0 MB
  • 4. Object Oriented Programming/3. Methods in Object Oriented Programming.mp4 24.8 MB
  • 14. Artificial Neural Network/6. Keras API in Artificial intelligence.mp4 24.4 MB
  • 14. Artificial Neural Network/1. What is Artificial Neural Network (ANN).mp4 24.1 MB
  • 9. Matplotlib/7. Grid, Spines, Ticks in python.mp4 23.5 MB
  • 19. Environment Installation for R/2. R Console Versus R Studio.mp4 23.0 MB
  • 3. Fundamentals of Python/7. Modules in Python.mp4 22.1 MB
  • 13. Machine Learning/4. What is Deep Learning.mp4 21.5 MB
  • 5. Python For Data Science Data Science/1. What Is Data Science.mp4 21.2 MB
  • 7. Pandas Using Pandas for Data Manipulation/1. What is Pandas.mp4 21.1 MB
  • 9. Matplotlib/1. What is Matplotlib.mp4 18.7 MB
  • 13. Machine Learning/13. Gathering data in Deep learning.mp4 18.5 MB
  • 6. Using Numpy for Data Manipulation/3. Array Operators in Numpy.mp4 18.4 MB
  • 4. Object Oriented Programming/1. Logic of Object Oriented Programming.mp4 17.2 MB
  • 13. Machine Learning/1. AI, Machine Learning and Deep Learning.mp4 17.0 MB
  • 2. Setting Up Python for Mac and Windows Python Data Science/4. Basics of Jupyter Notebook for Mac.mp4 15.5 MB
  • 1. Introduction to Complete Data Science, Deep Learning, R Data Science 2021/1. Be Smart and Use Data But How Answer is Data Science with Python.mp4 14.4 MB
  • 12. Data Science Hands-On Projects/3. Project II Bike Sharing.mp4 14.4 MB
  • 12. Data Science Hands-On Projects/7. Project IV English Premier League.mp4 14.1 MB
  • 21. Examining and Managing Data Structures in R/4. Test Functions in R.mp4 13.6 MB
  • 10. Seaborn/1. What is Seaborn.mp4 13.5 MB
  • 12. Data Science Hands-On Projects/5. Project III Housing and Property Sales.mp4 10.8 MB
  • 12. Data Science Hands-On Projects/1. Analyse Data With Different Data Sets Titanic Project.mp4 10.5 MB
  • 5. Python For Data Science Data Science/2. Data Literacy.mp4 10.2 MB
  • 3. Fundamentals of Python/9. Exercise Analyse in Python.mp4 6.0 MB
  • 10. Seaborn/5.3 salary.csv 3.4 MB
  • 12. Data Science Hands-On Projects/5.1 House Sales.csv 1.2 MB
  • 10. Seaborn/7.1 age_data.csv 677.3 kB
  • 9. Matplotlib/8.1 age_data.csv 677.3 kB
  • 12. Data Science Hands-On Projects/3.1 Bike_Share_London.csv 377.3 kB
  • 9. Matplotlib/9.1 winequality.csv 84.2 kB
  • 12. Data Science Hands-On Projects/1.2 Titanic.csv 58.7 kB
  • 12. Data Science Hands-On Projects/7.1 2006-2018 EPL stats.csv 55.2 kB
  • 9. Matplotlib/8. Basic Plots in Matplotlib I.srt 31.0 kB
  • 12. Data Science Hands-On Projects/4. Bike Sharing Project Answers.srt 30.7 kB
  • 12. Data Science Hands-On Projects/6. Answer for Housing and Property Sales Project.srt 29.1 kB
  • 12. Data Science Hands-On Projects/8. Answers for English Premier League Project.srt 28.8 kB
  • 13. Machine Learning/12. Unsupervised Machine Learning Methods.srt 27.2 kB
  • 11. Geoplotlib/2.1 poaching_points_cleaned.csv 24.8 kB
  • 10. Seaborn/5. Basic Plots in Seaborn.srt 22.8 kB
  • 8. Data Frame with Pandas/6. Missing Data and Data Munging in Pandas.srt 22.4 kB
  • 12. Data Science Hands-On Projects/2. Titanic Project Answers in python projects.srt 21.9 kB
  • 18. Projects Python projects, Data science projects, machine learning/2. Project - 2.srt 21.3 kB
  • 14. Artificial Neural Network/8. What is TensorFlow.srt 20.5 kB
  • 18. Projects Python projects, Data science projects, machine learning/1. Project - 1.srt 20.5 kB
  • 1. Introduction to Complete Data Science, Deep Learning, R Data Science 2021/3. FAQ about Complete data science with R, deep learning, machine learning.html 20.5 kB
  • 20. Data Management in R/3. Graphs and Charts in Python data science.srt 19.6 kB
  • 13. Machine Learning/11. Supervised Machine Learning Methods - 4.srt 19.2 kB
  • 7. Pandas Using Pandas for Data Manipulation/2. Series and Features.srt 19.2 kB
  • 17. Transfer Learning/1. What is Transfer Learning.srt 19.2 kB
  • 11. Geoplotlib/3. Example - 2.srt 19.0 kB
  • 27. Data Transformation in R/6. Grouped Summaries with Summarize Function in R.srt 18.0 kB
  • 3. Fundamentals of Python/5. Lists, Tuples, Dictionaries and Sets in Python.srt 17.9 kB
  • 9. Matplotlib/4. Figure, Subplot and Axes in Matplotlib.srt 17.7 kB
  • 15. Convolutional Neural Network (CNN)/1. What is CNN.srt 17.6 kB
  • 8. Data Frame with Pandas/10. Combining Data Frames Part – II.srt 17.6 kB
  • 8. Data Frame with Pandas/9. Combining Data Frames in Pandas.srt 17.5 kB
  • 13. Machine Learning/7. Machine Learning Methods.srt 16.4 kB
  • 13. Machine Learning/10. Supervised Machine Learning Methods - 3.srt 16.2 kB
  • 9. Matplotlib/9. Basic Plots in Matplotlib II.srt 16.0 kB
  • 10. Seaborn/7. Regression Plots and Squarify in Seaborn.srt 15.9 kB
  • 8. Data Frame with Pandas/8. How We Deal with Missing Data.srt 15.8 kB
  • 8. Data Frame with Pandas/1. Data Frame Attributes and Methods.srt 15.8 kB
  • 13. Machine Learning/9. Supervised Machine Learning Methods - 2.srt 15.6 kB
  • 27. Data Transformation in R/3. Filtering Rows with Filter Function in R programming.srt 15.5 kB
  • 18. Projects Python projects, Data science projects, machine learning/3. Project - 3.srt 15.3 kB
  • 6. Using Numpy for Data Manipulation/5. Numpy Exercises.srt 15.0 kB
  • 16. Recurrent Neural Network and LTSM/1. Understanding RNN and LSTM Networks.srt 14.9 kB
  • 18. Projects Python projects, Data science projects, machine learning/4. Project - 4.srt 14.9 kB
  • 10. Seaborn/4. Color Palettes in Seaborn.srt 14.9 kB
  • 14. Artificial Neural Network/3. Creating a Simple ANN in Artificial intelligence.srt 14.8 kB
  • 9. Matplotlib/5. Figure Customization in Matplotlib.srt 14.2 kB
  • 25. Data Frames/3. Manipulating Values in DF.srt 14.2 kB
  • 3. Fundamentals of Python/1. Data Types in Python.srt 13.8 kB
  • 13. Machine Learning/5. Learning representations from data.srt 13.7 kB
  • 13. Machine Learning/3. Turing Machine and Turing Test.srt 13.6 kB
  • 8. Data Frame with Pandas/5. Groupby Operations in Pandas.srt 12.5 kB
  • 27. Data Transformation in R/4. Arranging Rows with Arrange Function in R.srt 12.4 kB
  • 14. Artificial Neural Network/7. Optimizers in Artificial intelligence.srt 12.2 kB
  • 26. Factors in R/2. Manipulating Categorical Data with Forcats in R.srt 12.2 kB
  • 3. Fundamentals of Python/4. Loops in Python.srt 12.2 kB
  • 8. Data Frame with Pandas/4. Multi Index in Pandas.srt 12.1 kB
  • 8. Data Frame with Pandas/11. Work with Dataset Files in Pandas.srt 11.8 kB
  • 6. Using Numpy for Data Manipulation/2. Array and Features in Numpy Python.srt 11.7 kB
  • 11. Geoplotlib/4. Example - 3.srt 11.6 kB
  • 9. Matplotlib/8.2 scatter_ex.xlsx 11.6 kB
  • 8. Data Frame with Pandas/2. Data Frame Attributes and Methods Part – II.srt 11.5 kB
  • 14. Artificial Neural Network/4. Tensor Operations in Artificial intelligence.srt 11.2 kB
  • 10. Seaborn/2. Controlling Figure Aesthetics in Seaborn.srt 11.1 kB
  • 13. Machine Learning/6. Workflow of Machine Learning.srt 11.0 kB
  • 8. Data Frame with Pandas/7. Missing Data and Data Munging Part II.srt 11.0 kB
  • 10. Seaborn/6. Multi-Plots in Seaborn.srt 10.9 kB
  • 3. Fundamentals of Python/2. Operators in Python.srt 10.9 kB
  • 13. Machine Learning/8. Supervised Machine Learning Methods - 1.srt 10.6 kB
  • 14. Artificial Neural Network/2. Anatomy of Neural Network in Artificial intelligence.srt 10.6 kB
  • 11. Geoplotlib/1. What is Geoplotlib.srt 10.4 kB
  • 3. Fundamentals of Python/3. Conditionals in Python.srt 9.9 kB
  • 10. Seaborn/3. Example in Seaborn.srt 9.9 kB
  • 11. Geoplotlib/2. Example - 1.srt 9.8 kB
  • 8. Data Frame with Pandas/3. Data Frame Attributes and Methods Part – III.srt 9.5 kB
  • 4. Object Oriented Programming/5. Overriding and Overloading in OOP.srt 9.5 kB
  • 20. Data Management in R/2. Data Manipulation in R.srt 9.3 kB
  • 3. Fundamentals of Python/6. Data Type Operators and Methods in Python.srt 9.1 kB
  • 13. Machine Learning/15. Choosing the right algorithm and model in deep learning.srt 9.1 kB
  • 3. Fundamentals of Python/8. Functions in Python.srt 9.1 kB
  • 25. Data Frames/5. Tibbles in R.srt 8.8 kB
  • 6. Using Numpy for Data Manipulation/4. Indexing and Slicing in Numpy Python.srt 8.8 kB
  • 27. Data Transformation in R/1. Introduction to Data Transformation.srt 8.7 kB
  • 23. Arrays in R/2. Subsections of an Array in r programming.srt 8.5 kB
  • 9. Matplotlib/7. Grid, Spines, Ticks in python.srt 8.3 kB
  • 14. Artificial Neural Network/1. What is Artificial Neural Network (ANN).srt 8.3 kB
  • 14. Artificial Neural Network/6. Keras API in Artificial intelligence.srt 8.2 kB
  • 14. Artificial Neural Network/5. Tensor Operations 2.srt 8.1 kB
  • 13. Machine Learning/2. History of Machine Learning.srt 7.9 kB
  • 9. Matplotlib/2. Using Matplotlib.srt 7.6 kB
  • 13. Machine Learning/17. Evaluation in deep learning.srt 7.6 kB
  • 6. Using Numpy for Data Manipulation/1. What is Numpy.srt 7.5 kB
  • 9. Matplotlib/3. Pyplot – Pylab - Matplotlib.srt 7.4 kB
  • 20. Data Management in R/1. Getting Data into R.srt 7.3 kB
  • 13. Machine Learning/4. What is Deep Learning.srt 7.3 kB
  • 27. Data Transformation in R/2. Select Columns with Select Function in R programming.srt 7.1 kB
  • 4. Object Oriented Programming/2. Constructor in Object Oriented Programming.srt 7.0 kB
  • 27. Data Transformation in R/5. Adding New Variables with Mutate Function in R.srt 7.0 kB
  • 25. Data Frames/1. Introduction to Data Frames.srt 6.9 kB
  • 4. Object Oriented Programming/4. Inheritance in Object Oriented Programming.srt 6.8 kB
  • 24. Matrices in R programming/1. Matrices in R programming.srt 6.7 kB
  • 9. Matplotlib/6. Plot Customization in matplotlib.srt 6.7 kB
  • 5. Python For Data Science Data Science/1. What Is Data Science.srt 6.7 kB
  • 7. Pandas Using Pandas for Data Manipulation/1. What is Pandas.srt 6.5 kB
  • 3. Fundamentals of Python/10. Exercise Solution in Python.srt 6.5 kB
  • 13. Machine Learning/14. Data pre-processing in Deep learning.srt 6.4 kB
  • 13. Machine Learning/16. Training and testing the model.srt 6.4 kB
  • 2. Setting Up Python for Mac and Windows Python Data Science/2. Installing Anaconda for Mac, Python Data Science.srt 6.4 kB
  • 24. Matrices in R programming/3. Calculating With Matrices in Python Data science.srt 6.2 kB
  • 2. Setting Up Python for Mac and Windows Python Data Science/1. Installing Anaconda for Windows.srt 6.1 kB
  • 22. Lists in R/1. Lists in R.srt 5.9 kB
  • 2. Setting Up Python for Mac and Windows Python Data Science/3. Let's Meet Jupyter Notebook for Windows.srt 5.8 kB
  • 13. Machine Learning/13. Gathering data in Deep learning.srt 5.8 kB
  • 21. Examining and Managing Data Structures in R/7. Subsetting Vectors in R.srt 5.7 kB
  • 1. Introduction to Complete Data Science, Deep Learning, R Data Science 2021/1. Be Smart and Use Data But How Answer is Data Science with Python.srt 5.6 kB
  • 13. Machine Learning/1. AI, Machine Learning and Deep Learning.srt 5.6 kB
  • 21. Examining and Managing Data Structures in R/1. Vector Basics in R.srt 5.6 kB
  • 3. Fundamentals of Python/7. Modules in Python.srt 5.4 kB
  • 24. Matrices in R programming/2. Naming Matrix Row and Columns in R programming.srt 5.3 kB
  • 19. Environment Installation for R/2. R Console Versus R Studio.srt 5.3 kB
  • 4. Object Oriented Programming/1. Logic of Object Oriented Programming.srt 5.2 kB
  • 10. Seaborn/1. What is Seaborn.srt 5.1 kB
  • 12. Data Science Hands-On Projects/3. Project II Bike Sharing.srt 5.1 kB
  • 12. Data Science Hands-On Projects/7. Project IV English Premier League.srt 5.0 kB
  • 26. Factors in R/1. Introduction to Factors in R.srt 4.7 kB
  • 21. Examining and Managing Data Structures in R/5. Vector Recycling and Iterations in R.srt 4.7 kB
  • 23. Arrays in R/1. Arrays in r programming.srt 4.6 kB
  • 19. Environment Installation for R/1. Downloading and Installing R & R Studio.srt 4.5 kB
  • 12. Data Science Hands-On Projects/1. Analyse Data With Different Data Sets Titanic Project.srt 4.4 kB
  • 21. Examining and Managing Data Structures in R/6. Naming Vectors in R.srt 4.4 kB
  • 6. Using Numpy for Data Manipulation/3. Array Operators in Numpy.srt 4.3 kB
  • 4. Object Oriented Programming/3. Methods in Object Oriented Programming.srt 4.2 kB
  • 25. Data Frames/4. Adding and Removing Variables in R Programming.srt 3.9 kB
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