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-[Torch Code for character-level language models using LSTM](https://github.com/karpathy/char-rnn), [LSTM for Kaggle EEG Detection competition (Torch Code)](https://github.com/apaszke/kaggle-grasp-and-lift)
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-[LSTM for Sentiment Analysis in Theano](http://deeplearning.net/tutorial/lstm.html#lstm)
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-[Deep Learning for Visual Q&A | LSTM | CNN](http://avisingh599.github.io/deeplearning/visual-qa/), [Code](https://github.com/avisingh599/visual-qa)
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-[Computer Responds to email | Google](http://googleresearch.blogspot.in/2015/11/computer-respond-to-this-email.html)
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-[Computer Responds to email using LSTM | Google](http://googleresearch.blogspot.in/2015/11/computer-respond-to-this-email.html)
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-[LSTM dramatically improves Google Voice Search](http://googleresearch.blogspot.ch/2015/09/google-voice-search-faster-and-more.html), [2](http://deeplearning.net/2015/09/30/long-short-term-memory-dramatically-improves-google-voice-etc-now-available-to-a-billion-users/)
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-[Understanding Natural Language with Deep Neural Networks Using Torch](http://devblogs.nvidia.com/parallelforall/understanding-natural-language-deep-neural-networks-using-torch/)
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-[Understanding Natural Language with LSTM Using Torch](http://devblogs.nvidia.com/parallelforall/understanding-natural-language-deep-neural-networks-using-torch/)
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- Gated Recurrent Units (GRU)
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-[LSTM vs GRU](http://www.wildml.com/2015/10/recurrent-neural-network-tutorial-part-4-implementing-a-grulstm-rnn-with-python-and-theano/)
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