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awesome-rnn
Recurrent Neural Network - A curated list of resources dedicated to RNN
https://github.com/kjw0612/awesome-rnn
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- Tensorflow - Python, C++
- Get started
- Recurrent Neural Network Tutorial
- Sequence-to-Sequence Model Tutorial
- Tutorials
- Notebook examples
- Scikit Flow (skflow) - Simplified Scikit-learn like Interface for TensorFlow
- Keras - based modular deep learning library similar to Torch
- char-rnn-tensorflow - rnn in tensorflow
- Theano - Python
- tutorial on Theano
- Deep Learning Tutorials
- RNN for semantic parsing of speech
- LSTM network for sentiment analysis
- Pylearn2
- Blocks
- Keras - based modular deep learning library similar to Torch
- Lasagne
- theano-rnn
- Passage
- Theano-Lights
- Caffe - C++ with MATLAB/Python wrappers
- LRCN
- Torch - Lua
- torchnet
- char-rnn - layer RNN/LSTM/GRU for training/sampling from character-level language models
- torch-rnn - much faster and memory efficient reimplementation of char-rnn
- neuraltalk2
- LSTM
- Oxford - Machine Learning 2015 Practicals
- rnn
- PyTorch - Python
- Word-level RNN example
- Practical PyTorch tutorials
- Deep Learning For NLP In PyTorch
- DL4J
- Documentation - index.html), [Japanese](http://deeplearning4j.org/ja-index.html), [Korean](http://deeplearning4j.org/kr-index.html)) : [RNN](http://deeplearning4j.org/usingrnns.html), [LSTM](http://deeplearning4j.org/lstm.html)
- rnn examples
- Neon
- Brainstorm
- Chainer
- CGT
- RNNLIB
- RNNLM
- faster-RNNLM
- neuraltalk - based RNN/LSTM implementation
- gist
- Recurrentjs
- DARQN - Network
- CS224d
- Lecture Note 3
- Lecture Note 4 - directional RNN, GRU, LSTM
- CS231n
- Machine Learning
- Lecture 12
- Lecture 13
- Supervised Sequence Labelling with Recurrent Neural Networks
- Statistical Language Models based on Neural Networks
- Training Recurrent Neural Networks
- Recursive Deep Learning for Natural Language Processing and Computer Vision
- The Deep Learning Book chapter 10
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- [Paper-arXiv - ICML](http://jmlr.org/proceedings/papers/v37/chung15.pdf)] [[Supplementary](http://jmlr.org/proceedings/papers/v37/chung15-supp.pdf)]
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- Deep Learning
- LSTM: A Search Space Odyssey
- A Critical Review of Recurrent Neural Networks for Sequence Learning
- Visualizing and Understanding Recurrent Networks
- An Empirical Exploration of Recurrent Network Architectures
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- [Paper - Neural-Autoencoder)]
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- [Web - arXiv1](http://arxiv.org/pdf/1410.1090)], [[Paper-arXiv2](http://arxiv.org/pdf/1412.6632)]
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- [Paper-arXiv - CVPR](http://www.cs.cmu.edu/~xinleic/papers/cvpr15_rnn.pdf)]
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- OpenSLR
- LibriSpeech ASR corpus
- VoxForge
- Flickr 8k
- Flickr 30k
- Microsoft COCO
- The bAbI Project - Dataset for text understanding and reasoning, by Facebook AI Research. Contains:
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- SQuAD - Stanford Question Answering Dataset : [[Paper](http://arxiv.org/pdf/1606.05250)]
- DAQUAR - built upon [NYU Depth v2](http://cs.nyu.edu/~silberman/datasets/nyu_depth_v2.html) by N. Silberman et al.
- VQA - based on [MSCOCO](http://mscoco.org/) images
- Image QA - based on MSCOCO images
- Multilingual Image QA - built from scratch by Baidu - in Chinese, with English translation
- THUMOS - scale action recognition dataset
- MultiTHUMOS
- The Unreasonable Effectiveness of RNNs
- Understanding LSTM Networks
- WildML - neural-networks-tutorial-part-1-introduction-to-rnns/)], [[Part2](http://www.wildml.com/2015/09/recurrent-neural-networks-tutorial-part-2-implementing-a-language-model-rnn-with-python-numpy-and-theano/)], [[Part3](http://www.wildml.com/2015/10/recurrent-neural-networks-tutorial-part-3-backpropagation-through-time-and-vanishing-gradients/)], [[Part4](http://www.wildml.com/2015/10/recurrent-neural-network-tutorial-part-4-implementing-a-grulstm-rnn-with-python-and-theano/)]
- RNNs in Tensorflow, a Practical Guide and Undocumented Features
- Optimizing RNN Performance
- Character Level Language modelling using RNN
- Implement an RNN in Python
- LSTM Backpropogation
- Introduction to Recurrent Networks in TensorFlow
- Variable Sequence Lengths in TensorFlow
- Written Memories: Understanding, Deriving and Extending the LSTM
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