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| 01. 00 Luis Introducing Ortal Newtitle121217-oXv7GiC-jrM.en.vtt |
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| 01. 01 Welcome To The Deep Learning Program-3QPEmwq2NaE.mp4 |
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| 01. Actor-Critic Methods.html |
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| 01. Autoencoder Lesson Intro.html |
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| 01. Convolutional Layers.html |
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| 01. Introducing Ortal .html |
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| 01. Mean Squared Error Function.html |
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| 01. One Project Away!.html |
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| 01. On Keras.html |
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| 01. Overview.html |
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| 01. Project Description.html |
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| 01. Reinforcement Learning Lesson.html |
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| 01. Semi-supervised Learning.html |
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| 02. A Better Score Function.html |
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| 04. Games and Equilibria.html |
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| 04. Gradient Descent The Code.html |
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| 04. Gridworld Example.html |
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| 04. Implementation.html |
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| 04. Inspecting Variables.html |
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| 04. Launching the notebook server.html |
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| 04. Learning Rate.html |
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| 04. Learning Rate.html |
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| 04. Making Batches.html |
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| 04. Stochastic Policy Search.html |
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| 04. The Actor and The Critic.html |
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| 04. The Notebooks.html |
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| 04. Underfitting And Overfitting-xj4PlXMsN-Y.en.vtt |
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| 05. 04 RNN FFNN Reminder A V7 Final-_vrp2lZjXf0.en.vtt |
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| 05. Advantage Function.html |
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| 05. An Iterative Method, Part 1.html |
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| 05. Architecture in More Depth-rdAo4MqLbEk.en.vtt |
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| 05. Architectures in More Depth.html |
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| 05. Batches Solution.html |
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| 05. Books to Read.html |
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| 05. Building The Generator And Discriminator.html |
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| 05. Building the RNN.html |
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| 05. Character-wise RNN Notebook.html |
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| 05. Choosing Hyperparameters.html |
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| 05. Convolutional Autoencoders.html |
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| 05. Data Preparation.html |
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| 05. DCGAN and the Generator.html |
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| 05. Intuition.html |
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| 16. Implementation.html |
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| 17. Backpropagation Through Time (part a).html |
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| 17. Further Reading.html |
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| 17. Practical Aspects of Learning.html |
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| 20. Implementation.html |
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| 23. Conclusion.html |
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| 23. Momentum and Learning Rate Decay.html |
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| 25. 23 From RNNs To LSTMs V4 Final-MsqybcWmzGY.en.vtt |
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