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

  • 收录时间:2019-07-04 04:04:29
  • 文件大小:853MB
  • 下载次数:56
  • 最近下载:2021-01-20 14:53:52
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文件列表

  1. 6. Appendix/3. Windows-Focused Environment Setup 2018.vtt 186MB
  2. 6. Appendix/3. Windows-Focused Environment Setup 2018.mp4 186MB
  3. 6. Appendix/6. Proof that using Jupyter Notebook is the same as not using it.mp4 78MB
  4. 6. Appendix/4. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.mp4 44MB
  5. 6. Appendix/8. What order should I take your courses in (part 2).mp4 38MB
  6. 6. Appendix/2. Bonus Section on Machine Learning Basics.mp4 35MB
  7. 3. Pandas/7. .values vs .as_matrix().mp4 33MB
  8. 6. Appendix/7. What order should I take your courses in (part 1).mp4 29MB
  9. 6. Appendix/5. Python 2 vs Python 3.mp4 19MB
  10. 6. Appendix/1. Exercises.mp4 17MB
  11. 4. Matplotlib/4. Plotting Images.mp4 12MB
  12. 2. Numpy/7. More Matrix Operations.mp4 12MB
  13. 2. Numpy/1. Lists vs. Arrays.mp4 11MB
  14. 1. Introduction and Outline/1. What’s this course about How can you succeed What should you know first.mp4 10MB
  15. 5. Scipy/5. Other Interesting Scipy Functions.mp4 10MB
  16. 5. Scipy/1. Gaussian PDF and CDF.mp4 8MB
  17. 3. Pandas/3. More about DataFrames Selecting Rows and Columns.mp4 8MB
  18. 2. Numpy/2. Dot product 1 For loop vs. cosine method vs. dot function.mp4 8MB
  19. 3. Pandas/1. Manual Data Loading.mp4 8MB
  20. 1. Introduction and Outline/2. Where to get the code (and how to install libraries).mp4 7MB
  21. 5. Scipy/3. Sampling from a Gaussian Distribution (Spherical and Axis-aligned Elliptical).mp4 7MB
  22. 3. Pandas/2. DataFrames.mp4 7MB
  23. 4. Matplotlib/3. Histogram.mp4 7MB
  24. 2. Numpy/5. Generating Matrices to Work With.mp4 6MB
  25. 4. Matplotlib/2. Scatterplot.mp4 6MB
  26. 2. Numpy/4. Vectors and Matrices.mp4 6MB
  27. 3. Pandas/4. Even More about DataFrames Column Names.mp4 6MB
  28. 4. Matplotlib/1. Line Chart.mp4 6MB
  29. 3. Pandas/5. The apply() Function.mp4 5MB
  30. 5. Scipy/4. Sampling from a General Multivariate Normal.mp4 5MB
  31. 2. Numpy/8. Solving a Linear System.mp4 5MB
  32. 5. Scipy/2. Sampling from a Gaussian Distribution (1-D).mp4 4MB
  33. 2. Numpy/6. Matrix Products.mp4 4MB
  34. 3. Pandas/6. Joins.mp4 4MB
  35. 6. Appendix/9. Where to get Udemy coupons and FREE deep learning material.mp4 4MB
  36. 2. Numpy/9. Word Problem.mp4 3MB
  37. 2. Numpy/3. Dot product 2 Speed comparison.mp4 3MB
  38. 1. Introduction and Outline/4. Python 2 or Python 3.mp4 2MB
  39. 6. Appendix/8. What order should I take your courses in (part 2).vtt 20KB
  40. 6. Appendix/7. What order should I take your courses in (part 1).vtt 14KB
  41. 6. Appendix/4. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.vtt 12KB
  42. 6. Appendix/6. Proof that using Jupyter Notebook is the same as not using it.vtt 12KB
  43. 6. Appendix/1. Exercises.vtt 9KB
  44. 3. Pandas/7. .values vs .as_matrix().vtt 8KB
  45. 6. Appendix/2. Bonus Section on Machine Learning Basics.vtt 7KB
  46. 1. Introduction and Outline/1. What’s this course about How can you succeed What should you know first.vtt 7KB
  47. 2. Numpy/7. More Matrix Operations.vtt 7KB
  48. 2. Numpy/1. Lists vs. Arrays.vtt 6KB
  49. 5. Scipy/5. Other Interesting Scipy Functions.vtt 6KB
  50. 6. Appendix/5. Python 2 vs Python 3.vtt 5KB
  51. 5. Scipy/1. Gaussian PDF and CDF.vtt 5KB
  52. 3. Pandas/1. Manual Data Loading.vtt 5KB
  53. 2. Numpy/2. Dot product 1 For loop vs. cosine method vs. dot function.vtt 5KB
  54. 4. Matplotlib/4. Plotting Images.vtt 5KB
  55. 3. Pandas/3. More about DataFrames Selecting Rows and Columns.vtt 5KB
  56. 1. Introduction and Outline/2. Where to get the code (and how to install libraries).vtt 4KB
  57. 2. Numpy/4. Vectors and Matrices.vtt 4KB
  58. 3. Pandas/2. DataFrames.vtt 4KB
  59. 2. Numpy/5. Generating Matrices to Work With.vtt 3KB
  60. 4. Matplotlib/1. Line Chart.vtt 3KB
  61. 6. Appendix/9. Where to get Udemy coupons and FREE deep learning material.vtt 3KB
  62. 3. Pandas/4. Even More about DataFrames Column Names.vtt 3KB
  63. 4. Matplotlib/2. Scatterplot.vtt 3KB
  64. 2. Numpy/6. Matrix Products.vtt 3KB
  65. 3. Pandas/5. The apply() Function.vtt 3KB
  66. 4. Matplotlib/3. Histogram.vtt 3KB
  67. 5. Scipy/3. Sampling from a Gaussian Distribution (Spherical and Axis-aligned Elliptical).vtt 3KB
  68. 2. Numpy/8. Solving a Linear System.vtt 3KB
  69. 5. Scipy/4. Sampling from a General Multivariate Normal.vtt 2KB
  70. 3. Pandas/6. Joins.vtt 2KB
  71. 5. Scipy/2. Sampling from a Gaussian Distribution (1-D).vtt 1KB
  72. 2. Numpy/9. Word Problem.vtt 1KB
  73. 2. Numpy/3. Dot product 2 Speed comparison.vtt 1KB
  74. 1. Introduction and Outline/4. Python 2 or Python 3.vtt 1KB
  75. 1. Introduction and Outline/3. How will you practice what you've learned in this course.html 159B
  76. [FreeCourseLab.com].url 126B