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[] data-science-deep-learning-in-theano-tensorflow

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文件列表

  1. 09 Project Facial Expression Recognition/028 Class-Based ANN in Theano.mp4 44MB
  2. 10 Appendix/031 How to install Numpy Scipy Matplotlib Pandas IPython Theano and TensorFlow.mp4 44MB
  3. 09 Project Facial Expression Recognition/029 Class-Based ANN in TensorFlow.mp4 37MB
  4. 07 GPU Speedup Homework and Other Misc Topics/018 Setting up a GPU Instance on Amazon Web Services.mp4 26MB
  5. 10 Appendix/032 How to Code by Yourself part 1.mp4 25MB
  6. 06 TensorFlow/017 Building a neural network in TensorFlow.mp4 24MB
  7. 08 Modern Regularization Techniques/023 Dropout Regularization.mp4 23MB
  8. 05 Theano/015 Building a neural network in Theano.mp4 22MB
  9. 09 Project Facial Expression Recognition/025 Facial Expression Recognition Problem Description.mp4 21MB
  10. 05 Theano/014 Theano Basics Variables Functions Expressions Optimization.mp4 19MB
  11. 06 TensorFlow/016 TensorFlow Basics Variables Functions Expressions Optimization.mp4 17MB
  12. 10 Appendix/033 How to Code by Yourself part 2.mp4 15MB
  13. 03 Momentum and adaptive learning rates/008 Code for training a neural network using momentum.mp4 15MB
  14. 02 Gradient Descent Full vs Batch vs Stochastic/006 Full vs Batch vs Stochastic Gradient Descent in code.mp4 14MB
  15. 04 Choosing Hyperparameters/012 Grid Search in Code.mp4 14MB
  16. 09 Project Facial Expression Recognition/027 Utilities walkthrough.mp4 13MB
  17. 01 Outline the MNIST dataset and Linear Logistic Regression Benchmark/004 Where to get the MNIST dataset and Establishing a Linear Benchmark.mp4 11MB
  18. 03 Momentum and adaptive learning rates/010 Constant learning rate vs. RMSProp in Code.mp4 11MB
  19. 09 Project Facial Expression Recognition/026 The class imbalance problem.mp4 10MB
  20. 07 GPU Speedup Homework and Other Misc Topics/022 Theano vs. TensorFlow.mp4 9MB
  21. 01 Outline the MNIST dataset and Linear Logistic Regression Benchmark/003 How to Succeed in this Course.mp4 9MB
  22. 04 Choosing Hyperparameters/013 Random Search in Code.mp4 8MB
  23. 07 GPU Speedup Homework and Other Misc Topics/021 How to Improve your Theano and Tensorflow Skills.mp4 7MB
  24. 10 Appendix/030 Manually Choosing Learning Rate and Regularization Penalty.mp4 7MB
  25. 08 Modern Regularization Techniques/024 Dropout Intuition.mp4 6MB
  26. 01 Outline the MNIST dataset and Linear Logistic Regression Benchmark/002 Where does this course fit into your deep learning studies.mp4 6MB
  27. 02 Gradient Descent Full vs Batch vs Stochastic/005 What are full batch and stochastic gradient descent.mp4 6MB
  28. 04 Choosing Hyperparameters/011 Hyperparameter Optimization Cross-validation Grid Search and Random Search.mp4 6MB
  29. 07 GPU Speedup Homework and Other Misc Topics/019 Can Big Data be used to Speed Up Backpropagation.mp4 5MB
  30. 03 Momentum and adaptive learning rates/009 Variable and adaptive learning rates.mp4 5MB
  31. 01 Outline the MNIST dataset and Linear Logistic Regression Benchmark/001 Outline - what did you learn previously and what will you learn in this course.mp4 5MB
  32. 07 GPU Speedup Homework and Other Misc Topics/020 Exercises and Concepts Still to be Covered.mp4 4MB
  33. 03 Momentum and adaptive learning rates/007 Momentum.mp4 3MB
  34. Freetutorials.Us.url 119B
  35. [FreeTutorials.Us].txt 75B