# 第一周 循环序列模型（Recurrent Neural Networks）

- [1.1 为什么选择序列模型？（Why Sequence Models?）](https://baozoulin.gitbook.io/neural-networks-and-deep-learning/di-wu-men-ke-xu-lie-mo-xing-sequence-models/di-wu-men-kexulie-mo-578b28-sequence-models/recurrent-neural-networks/11-wei-shi-yao-xuan-ze-xu-lie-mo-xing-ff1f-ff08-why-sequence-models.md)
- [1.2 数学符号（Notation）](https://baozoulin.gitbook.io/neural-networks-and-deep-learning/di-wu-men-ke-xu-lie-mo-xing-sequence-models/di-wu-men-kexulie-mo-578b28-sequence-models/recurrent-neural-networks/12-shu-xue-fu-hao-ff08-notation.md)
- [1.3 循环神经网络模型（Recurrent Neural Network Model）](https://baozoulin.gitbook.io/neural-networks-and-deep-learning/di-wu-men-ke-xu-lie-mo-xing-sequence-models/di-wu-men-kexulie-mo-578b28-sequence-models/recurrent-neural-networks/13-xun-huan-shen-jing-wang-luo-mo-xing-ff08-recurrent-neural-network-model.md)
- [1.4 通过时间的反向传播（Backpropagation through time）](https://baozoulin.gitbook.io/neural-networks-and-deep-learning/di-wu-men-ke-xu-lie-mo-xing-sequence-models/di-wu-men-kexulie-mo-578b28-sequence-models/recurrent-neural-networks/14-tong-guo-shi-jian-de-fan-xiang-chuan-bo-ff08-backpropagation-through-time.md)
- [1.5 不同类型的循环神经网络（Different types of RNNs）](https://baozoulin.gitbook.io/neural-networks-and-deep-learning/di-wu-men-ke-xu-lie-mo-xing-sequence-models/di-wu-men-kexulie-mo-578b28-sequence-models/recurrent-neural-networks/15-bu-tong-lei-xing-dexun-huan-shen-jing-wang-luo-ff08-different-types-of-rnns.md)
- [1.6 语言模型和序列生成（Language model and sequence generation）](https://baozoulin.gitbook.io/neural-networks-and-deep-learning/di-wu-men-ke-xu-lie-mo-xing-sequence-models/di-wu-men-kexulie-mo-578b28-sequence-models/recurrent-neural-networks/16-yu-yan-mo-xinghe-xu-liesheng-cheng-ff08-language-model-and-sequence-generation.md)
- [1.7 对新序列采样（Sampling novel sequences）](https://baozoulin.gitbook.io/neural-networks-and-deep-learning/di-wu-men-ke-xu-lie-mo-xing-sequence-models/di-wu-men-kexulie-mo-578b28-sequence-models/recurrent-neural-networks/17-dui-xin-xu-lie-cai-yang-ff08-sampling-novel-sequences.md)
- [1.8 循环神经网络的梯度消失（Vanishing gradients with RNNs）](https://baozoulin.gitbook.io/neural-networks-and-deep-learning/di-wu-men-ke-xu-lie-mo-xing-sequence-models/di-wu-men-kexulie-mo-578b28-sequence-models/recurrent-neural-networks/18-xun-huan-shen-jing-wangluo-de-ti-du-xiao-shi-ff08-vanishing-gradients-with-rnns.md)
- [1.9 GRU单元（Gated Recurrent Unit（GRU））](https://baozoulin.gitbook.io/neural-networks-and-deep-learning/di-wu-men-ke-xu-lie-mo-xing-sequence-models/di-wu-men-kexulie-mo-578b28-sequence-models/recurrent-neural-networks/19-grudan-yuan-ff08-gated-recurrent-unit-gru.md)
- [1.10 长短期记忆（LSTM（long short term memory）unit）](https://baozoulin.gitbook.io/neural-networks-and-deep-learning/di-wu-men-ke-xu-lie-mo-xing-sequence-models/di-wu-men-kexulie-mo-578b28-sequence-models/recurrent-neural-networks/110-chang-duan-qi-ji-yi-ff08-lstm-long-short-term-memory-unit.md)
- [1.11 双向循环神经网络（Bidirectional RNN）](https://baozoulin.gitbook.io/neural-networks-and-deep-learning/di-wu-men-ke-xu-lie-mo-xing-sequence-models/di-wu-men-kexulie-mo-578b28-sequence-models/recurrent-neural-networks/111-shuang-xiang-xun-huan-shenjing-wang-luo-ff08-bidirectional-rnn.md)
- [1.12 深层循环神经网络（Deep RNNs）](https://baozoulin.gitbook.io/neural-networks-and-deep-learning/di-wu-men-ke-xu-lie-mo-xing-sequence-models/di-wu-men-kexulie-mo-578b28-sequence-models/recurrent-neural-networks/112-shen-ceng-xun-huan-shen-jing-wang-luo-ff08-deep-rnns.md)
- [Building your Recurrent Neural Network](https://baozoulin.gitbook.io/neural-networks-and-deep-learning/di-wu-men-ke-xu-lie-mo-xing-sequence-models/di-wu-men-kexulie-mo-578b28-sequence-models/recurrent-neural-networks/building+a+recurrent+neural+network+-+step+by+step+-+v3.md)
- [rnn\_utils.py](https://baozoulin.gitbook.io/neural-networks-and-deep-learning/di-wu-men-ke-xu-lie-mo-xing-sequence-models/di-wu-men-kexulie-mo-578b28-sequence-models/recurrent-neural-networks/rnnutils-py.md)
- [Dinosaurus Island -- Character level language model final](https://baozoulin.gitbook.io/neural-networks-and-deep-learning/di-wu-men-ke-xu-lie-mo-xing-sequence-models/di-wu-men-kexulie-mo-578b28-sequence-models/recurrent-neural-networks/dinosaurus+island+-+character+level+language+model+final+-+v3.md)
- [utils.py](https://baozoulin.gitbook.io/neural-networks-and-deep-learning/di-wu-men-ke-xu-lie-mo-xing-sequence-models/di-wu-men-kexulie-mo-578b28-sequence-models/recurrent-neural-networks/utilspy.md)
- [shakespeare\_utils.py](https://baozoulin.gitbook.io/neural-networks-and-deep-learning/di-wu-men-ke-xu-lie-mo-xing-sequence-models/di-wu-men-kexulie-mo-578b28-sequence-models/recurrent-neural-networks/shakespeareutils-py.md)
- [Improvise a Jazz Solo with an LSTM Network](https://baozoulin.gitbook.io/neural-networks-and-deep-learning/di-wu-men-ke-xu-lie-mo-xing-sequence-models/di-wu-men-kexulie-mo-578b28-sequence-models/recurrent-neural-networks/improvise+a+jazz+solo+with+an+lstm+network+-+v3.md)


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