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各种源码实现(tensorflow,torch,theano,keras,...)

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各种源码实现(tensorflow,torch,theano,keras,...) 深度学习 ##Table of Contents

##Tensorflow - [Neural Turing Machine(NMT)](https://github.com/carpedm20/NTM-tensorflow). - [A Neural Attention Model for Abstractive Summarization](https://github.com/BinbinBian/neural-summary-tensorflow) - [Recurrent Convolutional Memory Network](https://github.com/carpedm20/RCMN) - [End-To-End Memory Networks in Tensorflow](https://github.com/carpedm20/MemN2N-tensorflow) - [Neural Variational Inference for Text Processing](https://github.com/carpedm20/variational-text-tensorflow)---[wikiQA Corpus]() - [Word2Vec](https://github.com/carpedm20/word2vec-tensorflow) - [CNN code for insurance QA(question Answer matching)](https://github.com/BinbinBian/insuranceQA-cnn)---[InsuranceQA Corpus](https://github.com/shuzi/insuranceQA) - [Some experiments on MovieQA with Hsieh,Tom and Huang in AMLDS](https://github.com/YCKung/MovieQA) - [Teaching Machines to Read and Comprehend](https://github.com/carpedm20/attentive-reader-tensorflow) - [Convolutional Neural Networks for Sentence Classification (kIM.EMNLP2014)](https://github.com/dennybritz/cnn-text-classification-tf)Tensorflow - [Convolutional Neural Networks for Sentence Classification (kIM.EMNLP2014)](https://github.com/yoonkim/CNN_sentence)Theano - [Separating Answers from Queries for Neural Reading Comprehension](https://github.com/dirkweissenborn/qa_network) - [Neural Associative Memory for Dual-Sequence Modeling](https://github.com/dirkweissenborn/dual_am_rnn) - [The Ubuntu Dialogue Corpus: A Large Dataset for Research in Unstructured Multi-Turn Dialogue Systems.](https://github.com/dennybritz/chatbot-retrieval) ##Theano - [ End-To-End Memory Networks, formerly known as Weakly Supervised Memory Networks](https://github.com/npow/MemN2N) - [Memory Networks](https://github.com/npow/MemNN) - [Recurrent Neural Networks with External Memory for Language Understanding](https://github.com/npow/RNN-EM) - [Attention Sum Reader model as presented in "Text Comprehension with the Attention Sum Reader Network"](https://github.com/rkadlec/asreader)---[ CNN and Daily Mail news data QA]() - [character-level language models](https://github.com/lipiji/rnn-theano) - [Hierarchical Encoder-Decoder](https://github.com/BinbinBian/hierarchical-encoder-decoder) - [A Recurrent Latent Variable Model for Sequential Data](https://github.com/jych/nips2015_vrnn) ##Torch - [Sequence-to-sequence model with LSTM encoder/decoders and attention](https://github.com/harvardnlp/seq2seq-attn) - [Chains of Reasoning over Entities, Relations, and Text using Recurrent Neural Networks](https://github.com/rajarshd/ChainsOfReasoning/tree/master/model) - [Recurrent Memory Network for Language Modeling](https://github.com/ketranm/RMN) ##Matlab - [When Are Tree Structures Necessary for Deep Learning of Representations](https://github.com/jiweil/Sequence-Models-on-Stanford-Treebank) - ##Deep Reinforcement Learning ##machine learning and deep learning tutorials, articles and other resources - [machine learning and deep learning tutorials, articles and other resources](https://github.com/ujjwalkarn/Machine-Learning-Tutorials) - [Knowledge Graph Embeddings including TransE, TransH, TransR and PTransE](https://github.com/thunlp/KG2E) - [【论文:深度学习NLP的可视化理解】《Visualizing and Understanding Neural Models in NLP》J Li, X Chen, E Hovy, D Jurafsky (2015) ](https://github.com/jiweil/Visualizing-and-Understanding-Neural-Models-in-NLP) - [Links to the implementations of neural conversational models for different frameworks(seq2seq chatbot links)](https://github.com/nicolas-ivanov/seq2seq_chatbot_links) - [Links to the implementations of neural conversational models for different frameworks](https://github.com/nicolas-ivanov/seq2seq_chatbot_links) ##People -[carpedm20](https://github.com/carpedm20)

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