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Neural Networks

Convolutional Neural Networks

Readings

  1. http://ibillxia.github.io/blog/2013/04/06/Convolutional-Neural-Networks/ : 卷积神经网络（CNN）
  2. http://cs231n.github.io/convolutional-networks/ : Convolutional Neural Networks (CNNs / ConvNets) CS231n
  3. http://www.robots.ox.ac.uk/~vgg/practicals/cnn/ : VGG Convolutional Neural Networks Practical
  4. http://deeplearning.net/tutorial/lenet.html : Convolutional Neural Networks (LeNet)

Source code

TC

  1. https://github.com/yoonkim/CNN_sentence : Convolutional Neural Networks for Sentence Classification (EMNLP 2014)
  2. https://github.com/dennybritz/cnn-text-classification-tf : Implementing a CNN for Text Classification in Tensorflow

RE

  1. https://github.com/hadyelsahar/CNN-RelationExtraction : CNN-RelationExtraction (The CNN architecture implemented is inspired be Nguyen et al. 2015)
  2. https://github.com/sunilitggu/relation_extraction_in_clinical_text : Relation extraction from clinical texts using domain invariant convolutional neural network. BioNLP at ACL-2016
  3. https://github.com/thunlp/NRE : Neural Relation Extraction with Selective Attention over Instances. In Proceedings of ACL 2016

RNN

Source code

NER

  1. https://github.com/sunilitggu/disease_name_recognition_through_rnn : Recurrent neural network models for disease name recognition using domain invariant features. ACL-2016
  2. https://github.com/glample/tagger : Neural Architectures for Named Entity Recognition. NAACL 2016
  3. https://github.com/raghavchalapathy/dnr : An Investigation of Recurrent Neural Architectures for Drug Name Recognition. LOUHI 2016 : EMNLP 2016 Workshop
  4. https://github.com/raghavchalapathy/Bidirectional-LSTM-CRF-for-Clinical-Concept-Extraction : "Bidirectional LSTM-CRF for Clinical Concept Extraction" at Clinical Natural Language Processing Workshop at COLING 2016
  5. https://github.com/abhyudaynj/LSTM-CRF-models : Structured Prediction Models for RNN based Sequence Labeling in clinical text, EMNLP 2016.

Attention Networks

  1. https://github.com/harvardnlp/struct-attn : Structured Attention Networks

Word Embbeding

  1. https://github.com/3Top/word2vec-api : word2vec-api
  2. https://github.com/clinicalml/embeddings : Learning Low-Dimensional Representations of Medical Concepts

Chinese

  1. https://github.com/to-shimo/chinese-word2vec : word2vec/glove/swivel binary file on chinese corpus
  2. https://github.com/Kyubyong/wordvectors : Pre-trained word vectors of 30+ languages

Resources

Datasets

  1. http://deeplearning.net/datasets/ : deep learning datasets

Tools

  1. http://deeplearning.net/software_links/ : deep learning softwares
  2. https://github.com/tensorflow/tensorflow : TensorFlow
  3. https://github.com/tensorflow/fold : TensorFlow Fold (Deep learning with dynamic computation graphs in TensorFlow)
  4. https://github.com/tensorflow/playground : Play with neural networks! http://playground.tensorflow.org
  5. https://github.com/tflearn/tflearn : TFLearn: Deep learning library featuring a higher-level API for TensorFlow
  6. https://github.com/tensorflow/tensorflow/tree/master/tensorflow/tensorboard : TensorBoard
  7. https://github.com/Theano/Theano : Theano
  8. https://github.com/mnielsen/neural-networks-and-deep-learning : Code samples for "Neural Networks and Deep Learning"
  9. https://github.com/fchollet/keras : Deep Learning library for Python. Convnets, recurrent neural networks, and more. Runs on Theano or TensorFlow. http://keras-cn.readthedocs.io/en/latest/
  10. https://github.com/andersbll/deeppy : Deep learning in Python
  11. https://github.com/danielfrg/word2vec : Python interface to Google word2vec
  12. https://github.com/stanfordnlp/GloVe : GloVe: Global Vectors for Word Representation
  13. https://github.com/pytorch/pytorch: PyTorch

Readings

  1. http://deeplearning.net/reading-list/tutorials/ : deep learning tutorials
  2. https://github.com/terryum/awesome-deep-learning-papers : Awesome - Most Cited Deep Learning Papers
  3. https://github.com/andrewt3000/DL4NLP : Deep Learning for NLP resources (task-wise)
  4. https://github.com/shashankg7/Deep-Learning-for-NLP-Resources : Deep-Learning-for-NLP-Resources (classification-wise)
  5. https://github.com/oxford-cs-deepnlp-2017/lectures : Oxford Deep NLP 2017 course
  6. https://github.com/marekrei/theano-tutorial : Theano tutorial
  7. https://cs224d.stanford.edu/lectures/CS224d-Lecture7.pdf : CS224d: TensorFlow Tutorial
  8. https://github.com/tflearn/tflearn/blob/master/tutorials/intro/quickstart.md : TFLearn - Quick Start
  9. https://www.youtube.com/watch?v=bvHgESVuS6Q&feature=youtu.be : Learning TensorFlow (video: 40:41)
  10. http://jorditorres.org/first-contact-with-tensorflow/ : First contact with TensorFlow, get started with with Deep Learning programming
  11. https://github.com/aymericdamien/TensorFlow-Examples : TensorFlow Examples
  12. https://github.com/thunlp/NRLPapers : Must-read papers on NRL/NE
  13. http://cs231n.github.io/ : CS231n: Convolutional Neural Networks for Visual Recognition