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[UdemyCourseDownloader] Deep Learning Prerequisites Logistic Regression in Python

  • 收录时间:2019-03-22 23:28:40
  • 文件大小:425MB
  • 下载次数:77
  • 最近下载:2021-01-06 12:41:08
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文件列表

  1. 07 Appendix/036 How to install Numpy Scipy Matplotlib Pandas IPython Theano and TensorFlow.mp4 44MB
  2. 04 Practical concerns/026 The donut problem.mp4 25MB
  3. 07 Appendix/037 How to Code by Yourself part 1.mp4 25MB
  4. 06 Project Facial Expression Recognition/034 Facial Expression Recognition in Code.mp4 24MB
  5. 06 Project Facial Expression Recognition/031 Facial Expression Recognition Problem Description.mp4 21MB
  6. 03 Solving for the optimal weights/019 E-Commerce Course Project Training the Logistic Model.mp4 17MB
  7. 07 Appendix/038 How to Code by Yourself part 2.mp4 15MB
  8. 01 Start Here/004 Introduction to the E-Commerce Course Project.mp4 15MB
  9. 04 Practical concerns/021 L2 Regularization - Theory.mp4 15MB
  10. 04 Practical concerns/027 The XOR problem.mp4 14MB
  11. 06 Project Facial Expression Recognition/033 Utilities walkthrough.mp4 13MB
  12. 03 Solving for the optimal weights/016 Maximizing the likelihood.mp4 13MB
  13. 04 Practical concerns/024 L1 Regularization - Code.mp4 12MB
  14. 05 Checkpoint and applications How to make sure you know your stuff/028 BONUS Sentiment Analysis.mp4 11MB
  15. 02 Basics What is linear classification Whats the relation to neural networks/009 E-Commerce Course Project Pre-Processing the Data.mp4 11MB
  16. 06 Project Facial Expression Recognition/032 The class imbalance problem.mp4 10MB
  17. 03 Solving for the optimal weights/011 A closed-form solution to the Bayes classifier.mp4 10MB
  18. 03 Solving for the optimal weights/017 Updating the weights using gradient descent - Theory.mp4 9MB
  19. 03 Solving for the optimal weights/014 The cross-entropy error function - Code.mp4 9MB
  20. 01 Start Here/002 How to Succeed in this Course.mp4 9MB
  21. 07 Appendix/035 Gradient Descent Tutorial.mp4 8MB
  22. 02 Basics What is linear classification Whats the relation to neural networks/005 Linear Classification.mp4 8MB
  23. 01 Start Here/001 Introduction and Outline.mp4 8MB
  24. 02 Basics What is linear classification Whats the relation to neural networks/007 How do we calculate the output of a neuron logistic classifier - Theory.mp4 7MB
  25. 03 Solving for the optimal weights/018 Updating the weights using gradient descent - Code.mp4 7MB
  26. 03 Solving for the optimal weights/012 What do all these symbols mean X Y N D L J PY1X etc..mp4 6MB
  27. 04 Practical concerns/020 Interpreting the Weights.mp4 6MB
  28. 02 Basics What is linear classification Whats the relation to neural networks/008 How do we calculate the output of a neuron logistic classifier - Code.mp4 6MB
  29. 02 Basics What is linear classification Whats the relation to neural networks/010 E-Commerce Course Project Making Predictions.mp4 6MB
  30. 03 Solving for the optimal weights/015 Visualizing the linear discriminant Bayes classifier Gaussian clouds.mp4 5MB
  31. 05 Checkpoint and applications How to make sure you know your stuff/030 BONUS Exercises how to get good at this.mp4 5MB
  32. 04 Practical concerns/025 L1 vs L2 Regularization.mp4 5MB
  33. 03 Solving for the optimal weights/013 The cross-entropy error function - Theory.mp4 4MB
  34. 04 Practical concerns/022 L2 Regularization - Code.mp4 4MB
  35. 04 Practical concerns/023 L1 Regularization - Theory.mp4 4MB
  36. 02 Basics What is linear classification Whats the relation to neural networks/006 Biological inspiration - the neuron.mp4 4MB
  37. 05 Checkpoint and applications How to make sure you know your stuff/029 BONUS Where to get Udemy coupons and FREE deep learning material.mp4 4MB
  38. 01 Start Here/003 Review of the classification problem.mp4 3MB
  39. 01 Start Here/quizzes/001 Easy first quiz.html 2KB
  40. udemycoursedownloader.com.url 132B
  41. Udemy Course downloader.txt 94B