《深度學習進階：自然語言處理》中的網址

本文中的網址可能會在未予通知的情況下發生變更，敬請知悉。

P268中間（小鳥標記的小字部分）和P282上方（蠍子標記的小字部分）

從以下網址可以獲得學習好的權重：
https://www.oreilly.co.jp/pub/9784873118369/BetterRnnlm.pkl

參考文獻 P395

[1] Broadcasting
https://docs.scipy.org/doc/numpy-1.13.0/user/basics.broadcasting.html

[2] 100 numpy exercises
https://github.com/rougier/numpy-100

[3] CuPy web page
https://cupy.chainer.org/

[4] CuPy install page
https://docs-cupy.chainer.org/en/stable/install.html

P396

[10] Stanford University CS224d: Deep Learning for Natural Language Processing
http://cs224d.stanford.edu/

[11] Oxford Deep NLP 2017 course
https://github.com/oxford-cs-deepnlp-2017/lectures

[18] WordNet Interface
http://www.nltk.org/howto/wordnet.html

P397

[21] TruncatedSVD
http://scikit-learn.org/stable/modules/generated/sklearn.decomposition.TruncatedSVD.html

P398

[31] colah’s blog："Understanding LSTM Networks"
http://colah.github.io/posts/2015-08-Understanding-LSTMs/

P399

[39] PyTorch examples "Word-level language modeling RNN"
https://github.com/pytorch/examples/tree/0.3/word_language_model

[40] Keras examples "Implementation of sequence to sequence learning for performing addition of two numbers (as strings)"
https://github.com/keras-team/keras/blob/2.0.0/examples/addition_rnn.py

[47] Show and Tell: A Neural Image Caption Generator
https://github.com/tensorflow/models/tree/master/research/im2txt

P400

[51] Google Research Blog.
https://research.googleblog.com/2016/09/a-neural-network-for-machine.html

[53] Google Research Blog.
https://research.googleblog.com/2017/08/transformer-novel-neural-network.html

[57] DeepMind Blog："Differentiable neural computers"
https://deepmind.com/blog/differentiable-neural-computers/