Chapter05

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5.02 Understanding the LSTM cell.ipynb		5.02 Understanding the LSTM cell.ipynb
5.06 Predicting Bitcoins price using LSTM RNN.ipynb		5.06 Predicting Bitcoins price using LSTM RNN.ipynb
5.12 BiDirectional RNN.ipynb		5.12 BiDirectional RNN.ipynb
README.md		README.md

README.md

5.1. LSTM to the Rescue
5.2. Understanding the LSTM cell
5.3. Forward propagation in LSTM
5.4. Backpropagation in LSTM
5.5. Deriving backpropagation of LSTM Step by step
- 5.5.1. Gradients with respect to Gates
- 5.5.2. Gradients with respect to Weights
  - 5.5.2.1. Gradients with respect to V
  - 5.5.2.2. Gradients with respect to W
  - 5.5.2.3. Gradients with respect to U
5.6. Predicting Bitcoins price using LSTM
5.7. Gated Recurrent Units
5.8. Understanding GRU cell
- 5.8.1. Update Gate
- 5.8.2. Reset Gate
- 5.8.3. Updating the hidden state
5.9. Forward propagation in GRU cell
5.10. Deriving backpropagation in GRU cell
- 5.10.1. Gradients with respect to Gates
- 5.10.2. Gradients with respect to Weights
  - 5.10.2.1. Gradients with respect to V
  - 5.10.2.2. Gradients with respect to W
  - 5.10.2.3. Gradients with respect to U
5.11. Implementing GRU cell in Tensorflow
5.12. BiDirectional RNN
5.13. Going Deep with Deep RNN
5.14. Language Translation Seq2seq models
- 5.14.1. Encoder
- 5.14.2. Decoder
- 5.14.3. Attention Mechanism