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1. Artificial Neural Networks Section Introduction.mp4
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32.5 MB
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1. Deep Reinforcement Learning Section Introduction.mp4
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37.8 MB
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1. Differences Between Tensorflow 1.x and Tensorflow 2.x.mp4
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42.5 MB
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1. Embeddings.mp4
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58 MB
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1. GAN Theory.mp4
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86.5 MB
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1. Gradient Descent.mp4
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1. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.mp4
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166.7 MB
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1. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.srt
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1. Intro to Google Colab, how to use a GPU or TPU for free.mp4
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65.2 MB
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1. Intro to Google Colab, how to use a GPU or TPU for free.srt
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1. Introduction.mp4
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1. Links to TF2.0 Notebooks.html
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1. Mean Squared Error.mp4
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37.3 MB
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1. Recommender Systems with Deep Learning Theory.mp4
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68.7 MB
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1. Reinforcement Learning Stock Trader Introduction.mp4
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29.7 MB
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1. Sequence Data.mp4
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1. Transfer Learning Theory.mp4
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55.2 MB
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1. Transfer Learning Theory.srt
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1. What is Convolution (part 1).mp4
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83.6 MB
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1. What is Machine Learning.mp4
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1. What is a Web Service (Tensorflow Serving pt 1).mp4
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1. What is the Appendix.mp4
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18 MB
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1. What is the Appendix.srt
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10. BONUS Where to get discount coupons and FREE deep learning material.mp4
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37.8 MB
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10. BONUS Where to get discount coupons and FREE deep learning material.srt
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10. Batch Normalization.mp4
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10. Batch Normalization.srt
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10. Epsilon-Greedy.mp4
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10. Epsilon-Greedy.srt
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10. GRU and LSTM (pt 2).mp4
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10. GRU and LSTM (pt 2).srt
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11. A More Challenging Sequence.mp4
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11. A More Challenging Sequence.srt
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11. Improving CIFAR-10 Results.mp4
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11. Improving CIFAR-10 Results.srt
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11. Q-Learning.mp4
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11. Q-Learning.srt
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12. Deep Q-Learning DQN (pt 1).mp4
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12. Deep Q-Learning DQN (pt 1).srt
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12. Demo of the Long Distance Problem.mp4
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12. Demo of the Long Distance Problem.srt
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13. Deep Q-Learning DQN (pt 2).mp4
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13. Deep Q-Learning DQN (pt 2).srt
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13. RNN for Image Classification (Theory).mp4
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13. RNN for Image Classification (Theory).srt
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14. How to Learn Reinforcement Learning.mp4
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37.5 MB
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14. How to Learn Reinforcement Learning.srt
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14. RNN for Image Classification (Code).mp4
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14. RNN for Image Classification (Code).srt
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15. Stock Return Predictions using LSTMs (pt 1).mp4
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80 MB
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15. Stock Return Predictions using LSTMs (pt 1).srt
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16. Stock Return Predictions using LSTMs (pt 2).mp4
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16. Stock Return Predictions using LSTMs (pt 2).srt
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17. Stock Return Predictions using LSTMs (pt 3).mp4
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76.7 MB
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17. Stock Return Predictions using LSTMs (pt 3).srt
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2. Binary Cross Entropy.mp4
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21.5 MB
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2. Binary Cross Entropy.srt
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2. Code Preparation (Classification Theory).mp4
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68.5 MB
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2. Code Preparation (Classification Theory).srt
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2. Code Preparation (NLP).mp4
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62.9 MB
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2. Constants and Basic Computation.mp4
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2. Data and Environment.mp4
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56 MB
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2. Data and Environment.srt
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2. Elements of a Reinforcement Learning Problem.mp4
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97.8 MB
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2. Elements of a Reinforcement Learning Problem.srt
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2. Forecasting.mp4
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2. Forecasting.srt
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2. Forward Propagation.mp4
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2. GAN Code.mp4
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78.2 MB
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2. GAN Code.srt
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2. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.mp4
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117.1 MB
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2. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.srt
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2. Outline.mp4
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2. Outline.srt
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2. Recommender Systems with Deep Learning Code.mp4
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58.8 MB
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2. Recommender Systems with Deep Learning Code.srt
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11.7 KB
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2. Some Pre-trained Models (VGG, ResNet, Inception, MobileNet).mp4
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31.5 MB
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2. Some Pre-trained Models (VGG, ResNet, Inception, MobileNet).srt
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2. Stochastic Gradient Descent.mp4
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25 MB
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2. Stochastic Gradient Descent.srt
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2. Tensorflow 2.0 in Google Colab.mp4
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51.1 MB
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2. Tensorflow 2.0 in Google Colab.srt
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2. Tensorflow Serving pt 2.mp4
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124.5 MB
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2. Tensorflow Serving pt 2.srt
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20.4 KB
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2. What is Convolution (part 2).mp4
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25.2 MB
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2. What is Convolution (part 2).srt
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7.2 KB
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2. Windows-Focused Environment Setup 2018.mp4
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194 MB
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2. Windows-Focused Environment Setup 2018.srt
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20 KB
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3. Autoregressive Linear Model for Time Series Prediction.mp4
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87.7 MB
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3. Autoregressive Linear Model for Time Series Prediction.srt
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14.2 KB
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3. Categorical Cross Entropy.mp4
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35.4 MB
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3. Categorical Cross Entropy.srt
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3. Classification Notebook.mp4
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66.3 MB
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3. Classification Notebook.srt
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3. How to Code Yourself (part 1).mp4
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82.1 MB
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3. How to Code Yourself (part 1).srt
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22.1 KB
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3. Installing NVIDIA GPU-Accelerated Deep Learning Libraries on your Home Computer.mp4
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MP4
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167.3 MB
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3. Installing NVIDIA GPU-Accelerated Deep Learning Libraries on your Home Computer.srt
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32 KB
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3. Large Datasets and Data Generators.mp4
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36.6 MB
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3. Large Datasets and Data Generators.srt
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3. Momentum.mp4
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39.4 MB
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3. Momentum.srt
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3. Replay Buffer.mp4
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3. States, Actions, Rewards, Policies.mp4
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43 MB
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3. States, Actions, Rewards, Policies.srt
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11.3 KB
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3. Tensorflow Lite (TFLite).mp4
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42.4 MB
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3. Tensorflow Lite (TFLite).srt
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11 KB
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3. Text Preprocessing.mp4
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3. Text Preprocessing.srt
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3. The Geometrical Picture.mp4
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56.5 MB
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3. The Geometrical Picture.srt
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11.5 KB
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3. Uploading your own data to Google Colab.mp4
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89.1 MB
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3. Uploading your own data to Google Colab.srt
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12 KB
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3. Variables and Gradient Tape.mp4
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70.6 MB
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3. Variables and Gradient Tape.srt
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3. What is Convolution (part 3).mp4
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MP4
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27.6 MB
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3. What is Convolution (part 3).srt
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3. Where to get the code.mp4
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30.5 MB
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3. Where to get the code.srt
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4. 2 Approaches to Transfer Learning.mp4
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20.6 MB
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4. 2 Approaches to Transfer Learning.srt
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6 KB
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4. Activation Functions.mp4
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92.2 MB
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4. Activation Functions.srt
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22.6 KB
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4. Build Your Own Custom Model.mp4
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MP4
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70.2 MB
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4. Build Your Own Custom Model.srt
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13.3 KB
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4. Code Preparation (Regression Theory).mp4
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MP4
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31.3 MB
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4. Code Preparation (Regression Theory).srt
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4. Convolution on Color Images.mp4
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MP4
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77 MB
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4. Convolution on Color Images.srt
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20.6 KB
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4. How to Code Yourself (part 2).mp4
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MP4
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56.4 MB
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4. How to Code Yourself (part 2).srt
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13 KB
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4. Markov Decision Processes (MDPs).mp4
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MP4
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49 MB
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4. Markov Decision Processes (MDPs).srt
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4. Program Design and Layout.mp4
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29.8 MB
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4. Program Design and Layout.srt
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4. Proof that the Linear Model Works.mp4
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18.3 MB
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4. Proof that the Linear Model Works.srt
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4. Text Classification with LSTMs.mp4
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60.6 MB
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4. Text Classification with LSTMs.srt
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4. Variable and Adaptive Learning Rates.mp4
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38.5 MB
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4. Variable and Adaptive Learning Rates.srt
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15.2 KB
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4. Where can I learn about Numpy, Scipy, Matplotlib, Pandas, and Scikit-Learn.mp4
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MP4
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43.8 MB
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4. Where can I learn about Numpy, Scipy, Matplotlib, Pandas, and Scikit-Learn.srt
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11.5 KB
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4. Why is Google the King of Distributed Computing.mp4
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50.8 MB
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4. Why is Google the King of Distributed Computing.srt
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11.3 KB
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5. Adam.mp4
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42.6 MB
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5. Adam.srt
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5. CNN Architecture.mp4
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MP4
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90.9 MB
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5. CNN Architecture.srt
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27.9 KB
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5. CNNs for Text.mp4
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MP4
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40.9 MB
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5. CNNs for Text.srt
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9.6 KB
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5. Code pt 1.mp4
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MP4
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46.8 MB
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5. Code pt 1.srt
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7.2 KB
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5. Multiclass Classification.mp4
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MP4
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46.9 MB
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5. Multiclass Classification.srt
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11 KB
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5. Proof that using Jupyter Notebook is the same as not using it.mp4
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MP4
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77.9 MB
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5. Proof that using Jupyter Notebook is the same as not using it.srt
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14.2 KB
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5. Recurrent Neural Networks.mp4
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MP4
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92 MB
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5. Recurrent Neural Networks.srt
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SRT
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25.6 KB
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5. Regression Notebook.mp4
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MP4
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71.7 MB
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5. Regression Notebook.srt
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12.1 KB
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5. The Return.mp4
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MP4
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20.9 MB
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5. The Return.srt
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6.3 KB
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5. Training with Distributed Strategies.mp4
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MP4
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50.1 MB
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5. Training with Distributed Strategies.srt
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8.5 KB
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5. Transfer Learning Code (pt 1).mp4
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MP4
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66.6 MB
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5. Transfer Learning Code (pt 1).srt
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SRT
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13.8 KB
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6. CNN Code Preparation.mp4
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MP4
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86.3 MB
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6. CNN Code Preparation.srt
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19.6 KB
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6. Code pt 2.mp4
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MP4
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83.4 MB
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6. Code pt 2.srt
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11.8 KB
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6. How to Represent Images.mp4
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MP4
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80.9 MB
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6. How to Represent Images.srt
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SRT
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15.6 KB
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6. How to Succeed in this Course (Long Version).mp4
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MP4
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38.9 MB
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6. How to Succeed in this Course (Long Version).srt
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14.6 KB
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6. RNN Code Preparation.mp4
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MP4
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20.4 MB
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6. RNN Code Preparation.srt
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SRT
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7.1 KB
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6. Text Classification with CNNs.mp4
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MP4
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46.4 MB
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6. Text Classification with CNNs.srt
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SRT
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6.6 KB
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6. The Neuron.mp4
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MP4
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49.4 MB
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6. The Neuron.srt
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SRT
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12.5 KB
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6. Transfer Learning Code (pt 2).mp4
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MP4
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46.1 MB
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6. Transfer Learning Code (pt 2).srt
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SRT
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10.4 KB
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6. Using the TPU.html
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HTML
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1.8 KB
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6. Value Functions and the Bellman Equation.mp4
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MP4
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43.3 MB
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6. Value Functions and the Bellman Equation.srt
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12.5 KB
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7. CNN for Fashion MNIST.mp4
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MP4
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51.6 MB
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7. CNN for Fashion MNIST.srt
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SRT
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8 KB
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7. Code Preparation (ANN).mp4
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MP4
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56.2 MB
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7. Code Preparation (ANN).srt
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SRT
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16.3 KB
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7. Code pt 3.mp4
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MP4
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62.3 MB
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7. Code pt 3.srt
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SRT
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7.8 KB
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7. How does a model learn.mp4
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MP4
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55 MB
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7. How does a model learn.srt
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SRT
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14 KB
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7. Is Theano Dead.mp4
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MP4
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44.4 MB
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7. Is Theano Dead.srt
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12.6 KB
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7. RNN for Time Series Prediction.mp4
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87.2 MB
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7. RNN for Time Series Prediction.srt
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11.2 KB
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7. What does it mean to “learn”.mp4
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30.3 MB
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7. What does it mean to “learn”.srt
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8.9 KB
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8. ANN for Image Classification.mp4
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58.4 MB
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8. ANN for Image Classification.srt
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9.9 KB
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8. CNN for CIFAR-10.mp4
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34.8 MB
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8. CNN for CIFAR-10.srt
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5.4 KB
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8. Code pt 4.mp4
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59.2 MB
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8. Code pt 4.srt
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8.2 KB
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8. Making Predictions.mp4
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42 MB
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8. Making Predictions.srt
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8 KB
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8. Paying Attention to Shapes.mp4
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64.3 MB
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8. Paying Attention to Shapes.srt
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9.9 KB
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8. Solving the Bellman Equation with Reinforcement Learning (pt 1).mp4
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MP4
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39 MB
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8. Solving the Bellman Equation with Reinforcement Learning (pt 1).srt
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12.7 KB
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8. What order should I take your courses in (part 1).mp4
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88.1 MB
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8. What order should I take your courses in (part 1).srt
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16.1 KB
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9. ANN for Regression.mp4
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MP4
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84 MB
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9. ANN for Regression.srt
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12.8 KB
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9. Data Augmentation.mp4
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39.2 MB
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9. Data Augmentation.srt
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11.2 KB
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9. GRU and LSTM (pt 1).mp4
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76.1 MB
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9. GRU and LSTM (pt 1).srt
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21.1 KB
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9. Reinforcement Learning Stock Trader Discussion.mp4
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MP4
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18.2 MB
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9. Reinforcement Learning Stock Trader Discussion.srt
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4.4 KB
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9. Saving and Loading a Model.mp4
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35.3 MB
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9. Saving and Loading a Model.srt
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4.9 KB
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9. Solving the Bellman Equation with Reinforcement Learning (pt 2).mp4
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MP4
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52.5 MB
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9. Solving the Bellman Equation with Reinforcement Learning (pt 2).srt
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14.9 KB
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9. What order should I take your courses in (part 2).mp4
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MP4
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122.6 MB
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9. What order should I take your courses in (part 2).srt
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23 KB
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[GigaCourse.com].url
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![Udemy - Tensorflow 2.0: Deep Learning And Artificial Intelligence [GC]](/static/img/no-torrent-image.png "Udemy - Tensorflow 2.0: Deep Learning And Artificial Intelligence [GC]")
