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[] Udemy - Data Science Deep Learning in Python

  • 收录时间:2019-03-04 09:03:43
  • 文件大小:1GB
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文件列表

  1. 10. Appendix/3. Windows-Focused Environment Setup 2018.mp4 186MB
  2. 10. Appendix/9. Proof that using Jupyter Notebook is the same as not using it.mp4 78MB
  3. 1. Welcome/2. Where does this course fit into your deep learning studies.mp4 54MB
  4. 5. Training a neural network/8. Backpropagation in code.mp4 46MB
  5. 10. Appendix/4. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.mp4 44MB
  6. 7. TensorFlow, exercises, practice, and what to learn next/2. Visualizing what a neural network has learned using TensorFlow Playground.mp4 43MB
  7. 10. Appendix/8. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.mp4 39MB
  8. 2. Review/4. Neuron Training.mp4 39MB
  9. 10. Appendix/15. What order should I take your courses in (part 2).mp4 38MB
  10. 5. Training a neural network/4. How to Brace Yourself to Learn Backpropagation.mp4 37MB
  11. 4. Classifying more than 2 things at a time/6. Feedforward in Slow-Mo (part 1).mp4 30MB
  12. 10. Appendix/14. What order should I take your courses in (part 1).mp4 29MB
  13. 2. Review/2. What does machine learning do.mp4 26MB
  14. 6. Practical Machine Learning/4. Neural Networks for Regression.mp4 25MB
  15. 8. Project Facial Expression Recognition/5. Facial Expression Recognition in Code (Binary Sigmoid).mp4 25MB
  16. 10. Appendix/5. How to Code by Yourself (part 1).mp4 25MB
  17. 2. Review/3. Neuron Predictions.mp4 24MB
  18. 8. Project Facial Expression Recognition/7. Facial Expression Recognition in Code (ANN Softmax).mp4 23MB
  19. 1. Welcome/3. Where to get the code.mp4 23MB
  20. 9. Backpropagation Supplementary Lectures/3. Gradient Descent Tutorial.mp4 23MB
  21. 8. Project Facial Expression Recognition/2. Facial Expression Recognition Problem Description.mp4 21MB
  22. 5. Training a neural network/10. E-Commerce Course Project Training Logistic Regression with Softmax.mp4 20MB
  23. 8. Project Facial Expression Recognition/6. Facial Expression Recognition in Code (Logistic Regression Softmax).mp4 20MB
  24. 5. Training a neural network/5. Backpropagation Intro.mp4 19MB
  25. 9. Backpropagation Supplementary Lectures/5. Backpropagation with Softmax Troubleshooting.mp4 18MB
  26. 1. Welcome/4. How to Succeed in this Course.mp4 17MB
  27. 4. Classifying more than 2 things at a time/7. Feedforward in Slow-Mo (part 2).mp4 17MB
  28. 7. TensorFlow, exercises, practice, and what to learn next/1. TensorFlow plug-and-play example.mp4 16MB
  29. 9. Backpropagation Supplementary Lectures/2. Why Learn the Ins and Outs of Backpropagation.mp4 16MB
  30. 5. Training a neural network/11. E-Commerce Course Project Training a Neural Network.mp4 15MB
  31. 10. Appendix/6. How to Code by Yourself (part 2).mp4 15MB
  32. 3. Preliminaries From Neurons to Neural Networks/2. Introduction to the E-Commerce Course Project.mp4 15MB
  33. 10. Appendix/2. What's the difference between neural networks and deep learning.mp4 15MB
  34. 5. Training a neural network/2. What do all these symbols and letters mean.mp4 15MB
  35. 7. TensorFlow, exercises, practice, and what to learn next/6. Deep neural networks in just 3 lines of code with Sci-Kit Learn.mp4 14MB
  36. 2. Review/6. Review Section Summary.mp4 14MB
  37. 6. Practical Machine Learning/3. Donut and XOR Revisited.mp4 14MB
  38. 4. Classifying more than 2 things at a time/10. Building an entire feedforward neural network in Python.mp4 14MB
  39. 8. Project Facial Expression Recognition/4. Utilities walkthrough.mp4 13MB
  40. 10. Appendix/7. How to Succeed in this Course (Long Version).mp4 13MB
  41. 2. Review/1. Review Section Introduction.mp4 13MB
  42. 4. Classifying more than 2 things at a time/3. Interpreting the Weights of a Neural Network.mp4 13MB
  43. 6. Practical Machine Learning/6. Practical Considerations for Choosing Activation Functions.mp4 12MB
  44. 5. Training a neural network/7. Backpropagation - recursiveness.mp4 11MB
  45. 4. Classifying more than 2 things at a time/11. E-Commerce Course Project Pre-Processing the Data.mp4 11MB
  46. 5. Training a neural network/6. Backpropagation - what does the weight update depend on.mp4 10MB
  47. 8. Project Facial Expression Recognition/3. The class imbalance problem.mp4 10MB
  48. 8. Project Facial Expression Recognition/1. Facial Expression Recognition Project Introduction.mp4 10MB
  49. 5. Training a neural network/3. What does it mean to train a neural network.mp4 10MB
  50. 6. Practical Machine Learning/9. Practical Issues Section Summary.mp4 10MB
  51. 7. TensorFlow, exercises, practice, and what to learn next/5. How to get good at deep learning + exercises.mp4 9MB
  52. 4. Classifying more than 2 things at a time/1. Prediction Section Introduction and Outline.mp4 9MB
  53. 2. Review/5. Deep Learning Readiness Test.mp4 9MB
  54. 4. Classifying more than 2 things at a time/2. From Logistic Regression to Neural Networks.mp4 9MB
  55. 10. Appendix/13. Where does this course fit into your deep learning studies (Old Version).mp4 8MB
  56. 5. Training a neural network/12. Training Quiz.mp4 8MB
  57. 7. TensorFlow, exercises, practice, and what to learn next/4. You know more than you think you know.mp4 8MB
  58. 10. Appendix/12. Python 2 vs Python 3.mp4 8MB
  59. 4. Classifying more than 2 things at a time/9. Softmax in Code.mp4 8MB
  60. 6. Practical Machine Learning/8. Manually Choosing Learning Rate and Regularization Penalty.mp4 8MB
  61. 4. Classifying more than 2 things at a time/12. E-Commerce Course Project Making Predictions.mp4 8MB
  62. 3. Preliminaries From Neurons to Neural Networks/1. Neural Networks with No Math.mp4 7MB
  63. 6. Practical Machine Learning/7. Hyperparameters and Cross-Validation.mp4 7MB
  64. 5. Training a neural network/9. The WRONG Way to Learn Backpropagation.mp4 7MB
  65. 9. Backpropagation Supplementary Lectures/4. Help with Softmax Derivative.mp4 6MB
  66. 1. Welcome/1. Introduction and Outline.mp4 6MB
  67. 7. TensorFlow, exercises, practice, and what to learn next/3. Where to go from here.mp4 6MB
  68. 10. Appendix/1. What is the Appendix.mp4 5MB
  69. 10. Appendix/10. How to Uncompress a .tar.gz file.mp4 5MB
  70. 4. Classifying more than 2 things at a time/13. Prediction Quizzes.mp4 5MB
  71. 4. Classifying more than 2 things at a time/4. Softmax.mp4 5MB
  72. 5. Training a neural network/1. Training Section Introduction and Outline.mp4 4MB
  73. 5. Training a neural network/13. Training Section Summary.mp4 4MB
  74. 10. Appendix/11. BONUS Where to get Udemy coupons and FREE deep learning material.mp4 4MB
  75. 4. Classifying more than 2 things at a time/8. Where to get the code for this course.mp4 3MB
  76. 8. Project Facial Expression Recognition/8. Facial Expression Recognition Project Summary.mp4 3MB
  77. 4. Classifying more than 2 things at a time/14. Prediction Section Summary.mp4 3MB
  78. 6. Practical Machine Learning/1. Practical Issues Section Introduction and Outline.mp4 3MB
  79. 4. Classifying more than 2 things at a time/5. Sigmoid vs. Softmax.mp4 2MB
  80. 6. Practical Machine Learning/5. Common nonlinearities and their derivatives.mp4 2MB
  81. 6. Practical Machine Learning/2. Donut and XOR Review.mp4 2MB
  82. 9. Backpropagation Supplementary Lectures/1. Backpropagation Supplementary Lectures Introduction.mp4 2MB
  83. 10. Appendix/8. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.vtt 30KB
  84. 4. Classifying more than 2 things at a time/6. Feedforward in Slow-Mo (part 1).vtt 26KB
  85. 10. Appendix/15. What order should I take your courses in (part 2).vtt 22KB
  86. 10. Appendix/5. How to Code by Yourself (part 1).vtt 21KB
  87. 10. Appendix/3. Windows-Focused Environment Setup 2018.vtt 19KB
  88. 8. Project Facial Expression Recognition/2. Facial Expression Recognition Problem Description.vtt 16KB
  89. 10. Appendix/14. What order should I take your courses in (part 1).vtt 15KB
  90. 9. Backpropagation Supplementary Lectures/5. Backpropagation with Softmax Troubleshooting.vtt 15KB
  91. 4. Classifying more than 2 things at a time/7. Feedforward in Slow-Mo (part 2).vtt 14KB
  92. 1. Welcome/2. Where does this course fit into your deep learning studies.vtt 14KB
  93. 10. Appendix/4. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.vtt 14KB
  94. 10. Appendix/7. How to Succeed in this Course (Long Version).vtt 14KB
  95. 5. Training a neural network/2. What do all these symbols and letters mean.vtt 13KB
  96. 10. Appendix/9. Proof that using Jupyter Notebook is the same as not using it.vtt 13KB
  97. 3. Preliminaries From Neurons to Neural Networks/2. Introduction to the E-Commerce Course Project.vtt 13KB
  98. 5. Training a neural network/8. Backpropagation in code.vtt 13KB
  99. 10. Appendix/6. How to Code by Yourself (part 2).vtt 12KB
  100. 6. Practical Machine Learning/4. Neural Networks for Regression.vtt 12KB
  101. 9. Backpropagation Supplementary Lectures/2. Why Learn the Ins and Outs of Backpropagation.vtt 12KB
  102. 7. TensorFlow, exercises, practice, and what to learn next/6. Deep neural networks in just 3 lines of code with Sci-Kit Learn.vtt 12KB
  103. 2. Review/4. Neuron Training.vtt 11KB
  104. 6. Practical Machine Learning/6. Practical Considerations for Choosing Activation Functions.vtt 10KB
  105. 10. Appendix/2. What's the difference between neural networks and deep learning.vtt 10KB
  106. 4. Classifying more than 2 things at a time/3. Interpreting the Weights of a Neural Network.vtt 10KB
  107. 7. TensorFlow, exercises, practice, and what to learn next/2. Visualizing what a neural network has learned using TensorFlow Playground.vtt 9KB
  108. 5. Training a neural network/4. How to Brace Yourself to Learn Backpropagation.vtt 9KB
  109. 5. Training a neural network/3. What does it mean to train a neural network.vtt 9KB
  110. 6. Practical Machine Learning/9. Practical Issues Section Summary.vtt 9KB
  111. 8. Project Facial Expression Recognition/5. Facial Expression Recognition in Code (Binary Sigmoid).vtt 9KB
  112. 8. Project Facial Expression Recognition/7. Facial Expression Recognition in Code (ANN Softmax).vtt 9KB
  113. 5. Training a neural network/5. Backpropagation Intro.vtt 8KB
  114. 4. Classifying more than 2 things at a time/1. Prediction Section Introduction and Outline.vtt 8KB
  115. 2. Review/5. Deep Learning Readiness Test.vtt 7KB
  116. 7. TensorFlow, exercises, practice, and what to learn next/5. How to get good at deep learning + exercises.vtt 7KB
  117. 8. Project Facial Expression Recognition/3. The class imbalance problem.vtt 7KB
  118. 10. Appendix/13. Where does this course fit into your deep learning studies (Old Version).vtt 7KB
  119. 7. TensorFlow, exercises, practice, and what to learn next/1. TensorFlow plug-and-play example.vtt 7KB
  120. 2. Review/2. What does machine learning do.vtt 7KB
  121. 4. Classifying more than 2 things at a time/2. From Logistic Regression to Neural Networks.vtt 7KB
  122. 7. TensorFlow, exercises, practice, and what to learn next/4. You know more than you think you know.vtt 7KB
  123. 8. Project Facial Expression Recognition/6. Facial Expression Recognition in Code (Logistic Regression Softmax).vtt 7KB
  124. 5. Training a neural network/12. Training Quiz.vtt 7KB
  125. 3. Preliminaries From Neurons to Neural Networks/1. Neural Networks with No Math.vtt 6KB
  126. 5. Training a neural network/10. E-Commerce Course Project Training Logistic Regression with Softmax.vtt 6KB
  127. 6. Practical Machine Learning/7. Hyperparameters and Cross-Validation.vtt 6KB
  128. 1. Welcome/1. Introduction and Outline.vtt 6KB
  129. 8. Project Facial Expression Recognition/1. Facial Expression Recognition Project Introduction.vtt 6KB
  130. 10. Appendix/12. Python 2 vs Python 3.vtt 6KB
  131. 1. Welcome/3. Where to get the code.vtt 6KB
  132. 7. TensorFlow, exercises, practice, and what to learn next/3. Where to go from here.vtt 6KB
  133. 2. Review/3. Neuron Predictions.vtt 6KB
  134. 6. Practical Machine Learning/8. Manually Choosing Learning Rate and Regularization Penalty.vtt 5KB
  135. 8. Project Facial Expression Recognition/4. Utilities walkthrough.vtt 5KB
  136. 5. Training a neural network/9. The WRONG Way to Learn Backpropagation.vtt 5KB
  137. 4. Classifying more than 2 things at a time/11. E-Commerce Course Project Pre-Processing the Data.vtt 5KB
  138. 9. Backpropagation Supplementary Lectures/3. Gradient Descent Tutorial.vtt 5KB
  139. 4. Classifying more than 2 things at a time/10. Building an entire feedforward neural network in Python.vtt 5KB
  140. 2. Review/6. Review Section Summary.vtt 5KB
  141. 9. Backpropagation Supplementary Lectures/4. Help with Softmax Derivative.vtt 5KB
  142. 5. Training a neural network/11. E-Commerce Course Project Training a Neural Network.vtt 5KB
  143. 6. Practical Machine Learning/3. Donut and XOR Revisited.vtt 4KB
  144. 4. Classifying more than 2 things at a time/13. Prediction Quizzes.vtt 4KB
  145. 5. Training a neural network/1. Training Section Introduction and Outline.vtt 4KB
  146. 10. Appendix/10. How to Uncompress a .tar.gz file.vtt 4KB
  147. 4. Classifying more than 2 things at a time/4. Softmax.vtt 4KB
  148. 5. Training a neural network/13. Training Section Summary.vtt 4KB
  149. 1. Welcome/4. How to Succeed in this Course.vtt 4KB
  150. 4. Classifying more than 2 things at a time/9. Softmax in Code.vtt 4KB
  151. 4. Classifying more than 2 things at a time/12. E-Commerce Course Project Making Predictions.vtt 3KB
  152. 10. Appendix/1. What is the Appendix.vtt 3KB
  153. 10. Appendix/11. BONUS Where to get Udemy coupons and FREE deep learning material.vtt 3KB
  154. 5. Training a neural network/6. Backpropagation - what does the weight update depend on.vtt 3KB
  155. 2. Review/1. Review Section Introduction.vtt 3KB
  156. 4. Classifying more than 2 things at a time/14. Prediction Section Summary.vtt 3KB
  157. 6. Practical Machine Learning/1. Practical Issues Section Introduction and Outline.vtt 2KB
  158. 5. Training a neural network/7. Backpropagation - recursiveness.vtt 2KB
  159. 4. Classifying more than 2 things at a time/8. Where to get the code for this course.vtt 2KB
  160. 6. Practical Machine Learning/5. Common nonlinearities and their derivatives.vtt 2KB
  161. 4. Classifying more than 2 things at a time/5. Sigmoid vs. Softmax.vtt 2KB
  162. 8. Project Facial Expression Recognition/8. Facial Expression Recognition Project Summary.vtt 2KB
  163. 6. Practical Machine Learning/2. Donut and XOR Review.vtt 2KB
  164. 9. Backpropagation Supplementary Lectures/1. Backpropagation Supplementary Lectures Introduction.vtt 1KB
  165. [FreeCourseLab.com].url 126B