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[] Udemy - Deep Learning Prerequisites Logistic Regression in Python

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文件列表

  1. 8. Setting Up Your Environment/1. Windows-Focused Environment Setup 2018.mp4 186MB
  2. 9. Extra Help With Python Coding for Beginners/4. Proof that using Jupyter Notebook is the same as not using it.mp4 78MB
  3. 3/2. Define the multi-dimensional problem and derive the solution.mp4 60MB
  4. 1. Start Here/3. Statistics vs. Machine Learning.mp4 56MB
  5. 8. Setting Up Your Environment/2. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.mp4 44MB
  6. 10. Effective Learning Strategies for Machine Learning/2. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.mp4 39MB
  7. 11. Appendix FAQ/2. BONUS Where to get discount coupons and FREE deep learning material.mp4 38MB
  8. 10. Effective Learning Strategies for Machine Learning/4. What order should I take your courses in (part 2).mp4 38MB
  9. 10. Effective Learning Strategies for Machine Learning/3. What order should I take your courses in (part 1).mp4 29MB
  10. 1. Start Here/2. How to Succeed in this Course.mp4 28MB
  11. 4. Practical concerns/8. The donut problem.mp4 25MB
  12. 2/2. Define the model in 1-D, derive the solution.mp4 25MB
  13. 9. Extra Help With Python Coding for Beginners/2. How to Code by Yourself (part 1).mp4 25MB
  14. 6. Project Facial Expression Recognition/5. Facial Expression Recognition in Code.mp4 24MB
  15. 4. Practical concerns/10. Why Divide by Square Root of D.mp4 23MB
  16. 7. Background Review/1. Gradient Descent Tutorial.mp4 23MB
  17. 6. Project Facial Expression Recognition/2. Facial Expression Recognition Problem Description.mp4 21MB
  18. 2/9. Moore's Law Derivation.mp4 20MB
  19. 2/5. Determine how good the model is - r-squared.mp4 20MB
  20. 2/1. Define the model in 1-D, derive the solution (Updated Version).mp4 19MB
  21. 2/8. Demonstrating Moore's Law in Code.mp4 17MB
  22. 3/5. Polynomial regression - extending linear regression (with Python code).mp4 16MB
  23. 2/11. Suggestion Box.mp4 16MB
  24. 3/4. Coding the multi-dimensional solution in Python.mp4 15MB
  25. 9. Extra Help With Python Coding for Beginners/3. How to Code by Yourself (part 2).mp4 15MB
  26. 1. Start Here/5. Introduction to the E-Commerce Course Project.mp4 15MB
  27. 4. Practical concerns/3. L2 Regularization - Theory.mp4 15MB
  28. 3/1. Define the multi-dimensional problem and derive the solution (Updated Version).mp4 14MB
  29. 2/3. Coding the 1-D solution in Python.mp4 14MB
  30. 4. Practical concerns/9. The XOR problem.mp4 14MB
  31. 1. Start Here/1. Introduction and Outline.mp4 14MB
  32. 6. Project Facial Expression Recognition/4. Utilities walkthrough.mp4 13MB
  33. 10. Effective Learning Strategies for Machine Learning/1. How to Succeed in this Course (Long Version).mp4 13MB
  34. 3/6. Predicting Systolic Blood Pressure from Age and Weight.mp4 12MB
  35. 4. Practical concerns/6. L1 Regularization - Code.mp4 12MB
  36. 5. Checkpoint and applications How to make sure you know your stuff/1. BONUS Sentiment Analysis.mp4 11MB
  37. 6. Project Facial Expression Recognition/3. The class imbalance problem.mp4 10MB
  38. 6. Project Facial Expression Recognition/1. Facial Expression Recognition Project Introduction.mp4 10MB
  39. 9. Extra Help With Python Coding for Beginners/5. Python 2 vs Python 3.mp4 8MB
  40. 4. Practical concerns/2. Interpreting the Weights.mp4 6MB
  41. 11. Appendix FAQ/1. What is the Appendix.mp4 5MB
  42. 9. Extra Help With Python Coding for Beginners/1. How to Uncompress a .tar.gz file.mp4 5MB
  43. 5. Checkpoint and applications How to make sure you know your stuff/2. BONUS Exercises + how to get good at this.mp4 5MB
  44. 4. Practical concerns/7. L1 vs L2 Regularization.mp4 5MB
  45. 4. Practical concerns/1. Practical Section Introduction.mp4 5MB
  46. 2/6. R-squared in code.mp4 4MB
  47. 4. Practical concerns/4. L2 Regularization - Code.mp4 4MB
  48. 4. Practical concerns/5. L1 Regularization - Theory.mp4 4MB
  49. 2/7. Introduction to Moore's Law Problem.mp4 4MB
  50. 3/7. R-squared Quiz 2.mp4 3MB
  51. 4. Practical concerns/11. Practical Section Summary.mp4 3MB
  52. 3/3. How to solve multiple linear regression using only matrices.mp4 3MB
  53. 1. Start Here/4. Review of the classification problem.mp4 3MB
  54. 6. Project Facial Expression Recognition/6. Facial Expression Recognition Project Summary.mp4 3MB
  55. 2/10. R-squared Quiz 1.mp4 3MB
  56. 2/4. Exercise Theory vs. Code.mp4 1MB
  57. 10. Effective Learning Strategies for Machine Learning/2. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.srt 34KB
  58. 10. Effective Learning Strategies for Machine Learning/4. What order should I take your courses in (part 2).srt 25KB
  59. 9. Extra Help With Python Coding for Beginners/2. How to Code by Yourself (part 1).srt 24KB
  60. 8. Setting Up Your Environment/1. Windows-Focused Environment Setup 2018.srt 22KB
  61. 2/1. Define the model in 1-D, derive the solution (Updated Version).srt 18KB
  62. 10. Effective Learning Strategies for Machine Learning/3. What order should I take your courses in (part 1).srt 17KB
  63. 1. Start Here/3. Statistics vs. Machine Learning.srt 16KB
  64. 6. Project Facial Expression Recognition/2. Facial Expression Recognition Problem Description.srt 16KB
  65. 10. Effective Learning Strategies for Machine Learning/1. How to Succeed in this Course (Long Version).srt 16KB
  66. 8. Setting Up Your Environment/2. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.srt 15KB
  67. 9. Extra Help With Python Coding for Beginners/4. Proof that using Jupyter Notebook is the same as not using it.srt 15KB
  68. 9. Extra Help With Python Coding for Beginners/3. How to Code by Yourself (part 2).srt 14KB
  69. 1. Start Here/5. Introduction to the E-Commerce Course Project.srt 14KB
  70. 3/2. Define the multi-dimensional problem and derive the solution.srt 13KB
  71. 3/1. Define the multi-dimensional problem and derive the solution (Updated Version).srt 12KB
  72. 4. Practical concerns/3. L2 Regularization - Theory.srt 12KB
  73. 2/2. Define the model in 1-D, derive the solution.srt 11KB
  74. 4. Practical concerns/10. Why Divide by Square Root of D.srt 9KB
  75. 1. Start Here/2. How to Succeed in this Course.srt 9KB
  76. 11. Appendix FAQ/2. BONUS Where to get discount coupons and FREE deep learning material.srt 8KB
  77. 2/9. Moore's Law Derivation.srt 8KB
  78. 6. Project Facial Expression Recognition/5. Facial Expression Recognition in Code.srt 8KB
  79. 6. Project Facial Expression Recognition/3. The class imbalance problem.srt 8KB
  80. 4. Practical concerns/8. The donut problem.srt 7KB
  81. 2/8. Demonstrating Moore's Law in Code.srt 7KB
  82. 6. Project Facial Expression Recognition/1. Facial Expression Recognition Project Introduction.srt 7KB
  83. 9. Extra Help With Python Coding for Beginners/5. Python 2 vs Python 3.srt 7KB
  84. 5. Checkpoint and applications How to make sure you know your stuff/1. BONUS Sentiment Analysis.srt 6KB
  85. 4. Practical concerns/9. The XOR problem.srt 6KB
  86. 7. Background Review/1. Gradient Descent Tutorial.srt 6KB
  87. 2/3. Coding the 1-D solution in Python.srt 6KB
  88. 6. Project Facial Expression Recognition/4. Utilities walkthrough.srt 6KB
  89. 3/4. Coding the multi-dimensional solution in Python.srt 6KB
  90. 3/6. Predicting Systolic Blood Pressure from Age and Weight.srt 5KB
  91. 1. Start Here/1. Introduction and Outline.srt 5KB
  92. 3/5. Polynomial regression - extending linear regression (with Python code).srt 5KB
  93. 4. Practical concerns/2. Interpreting the Weights.srt 5KB
  94. 4. Practical concerns/6. L1 Regularization - Code.srt 5KB
  95. 2/11. Suggestion Box.srt 5KB
  96. 2/5. Determine how good the model is - r-squared.srt 5KB
  97. 4. Practical concerns/7. L1 vs L2 Regularization.srt 4KB
  98. 9. Extra Help With Python Coding for Beginners/1. How to Uncompress a .tar.gz file.srt 4KB
  99. 4. Practical concerns/5. L1 Regularization - Theory.srt 4KB
  100. 5. Checkpoint and applications How to make sure you know your stuff/2. BONUS Exercises + how to get good at this.srt 4KB
  101. 11. Appendix FAQ/1. What is the Appendix.srt 4KB
  102. 4. Practical concerns/1. Practical Section Introduction.srt 4KB
  103. 2/7. Introduction to Moore's Law Problem.srt 4KB
  104. 3/7. R-squared Quiz 2.srt 3KB
  105. 4. Practical concerns/11. Practical Section Summary.srt 3KB
  106. 1. Start Here/4. Review of the classification problem.srt 2KB
  107. 2/10. R-squared Quiz 1.srt 2KB
  108. 3/3. How to solve multiple linear regression using only matrices.srt 2KB
  109. 2/6. R-squared in code.srt 2KB
  110. 6. Project Facial Expression Recognition/6. Facial Expression Recognition Project Summary.srt 2KB
  111. 4. Practical concerns/4. L2 Regularization - Code.srt 2KB
  112. 2/4. Exercise Theory vs. Code.srt 2KB
  113. 1. Start Here/6. Easy first quiz.html 152B
  114. [Tutorialsplanet.NET].url 128B