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[FreeCourseLab.com] Udemy - Deep Learning Prerequisites The Numpy Stack in Python

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视频 2020-1-2 05:01 2024-12-26 00:00 222 666.25 MB 37
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文件列表
  1. 1. Introduction and Outline/1. What’s this course about How can you succeed What should you know first.mp410.16MB
  2. 1. Introduction and Outline/2. Where to get the code (and how to install libraries).mp47.5MB
  3. 1. Introduction and Outline/4. Python 2 or Python 3.mp41.82MB
  4. 2. Numpy/1. Lists vs. Arrays.mp410.67MB
  5. 2. Numpy/2. Dot product 1 For loop vs. cosine method vs. dot function.mp48.17MB
  6. 2. Numpy/3. Dot product 2 Speed comparison.mp43.13MB
  7. 2. Numpy/4. Vectors and Matrices.mp46.16MB
  8. 2. Numpy/5. Generating Matrices to Work With.mp46.37MB
  9. 2. Numpy/6. Matrix Products.mp44.41MB
  10. 2. Numpy/7. More Matrix Operations.mp412.05MB
  11. 2. Numpy/8. Solving a Linear System.mp44.59MB
  12. 2. Numpy/9. Word Problem.mp43.33MB
  13. 3. Pandas/1. Manual Data Loading.mp48.13MB
  14. 3. Pandas/2. DataFrames.mp46.94MB
  15. 3. Pandas/3. More about DataFrames Selecting Rows and Columns.mp48.23MB
  16. 3. Pandas/4. Even More about DataFrames Column Names.mp45.81MB
  17. 3. Pandas/5. The apply() Function.mp45.39MB
  18. 3. Pandas/6. Joins.mp44.03MB
  19. 3. Pandas/7. .values vs .as_matrix().mp433.28MB
  20. 4. Matplotlib/1. Line Chart.mp45.55MB
  21. 4. Matplotlib/2. Scatterplot.mp46.24MB
  22. 4. Matplotlib/3. Histogram.mp46.52MB
  23. 4. Matplotlib/4. Plotting Images.mp412.16MB
  24. 5. Scipy/1. Gaussian PDF and CDF.mp48.45MB
  25. 5. Scipy/2. Sampling from a Gaussian Distribution (1-D).mp44.5MB
  26. 5. Scipy/3. Sampling from a Gaussian Distribution (Spherical and Axis-aligned Elliptical).mp47.49MB
  27. 5. Scipy/4. Sampling from a General Multivariate Normal.mp45.03MB
  28. 5. Scipy/5. Other Interesting Scipy Functions.mp410MB
  29. 6. Appendix/1. Exercises.mp416.69MB
  30. 6. Appendix/2. Bonus Section on Machine Learning Basics.mp434.96MB
  31. 6. Appendix/3. Windows-Focused Environment Setup 2018.mp4186.24MB
  32. 6. Appendix/4. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.mp443.92MB
  33. 6. Appendix/5. Python 2 vs Python 3.mp419.1MB
  34. 6. Appendix/6. Proof that using Jupyter Notebook is the same as not using it.mp478.28MB
  35. 6. Appendix/7. What order should I take your courses in (part 1).mp429.33MB
  36. 6. Appendix/8. What order should I take your courses in (part 2).mp437.63MB
  37. 6. Appendix/9. Where to get Udemy coupons and FREE deep learning material.mp44.02MB
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