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Added "LSTM Human Activity Recognition" #20

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1 change: 1 addition & 0 deletions README.md
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Expand Up @@ -53,6 +53,7 @@ Last Update: 2016.08.09
| [Blocks](https://github.com/mila-udem/blocks) | 866 | A Theano framework for building and training neural networks.
| [TDB](https://github.com/ericjang/tdb) | 860 | Interactive, node-by-node debugging and visualization for TensorFlow.
| [Scikit Neural Net](https://github.com/aigamedev/scikit-neuralnetwork) | 849 | Deep neural networks without the learning cliff! Classifiers and regressors compatible with scikit-learn.
| [LSTM Human Activity Recognition](https://github.com/guillaume-chevalier/LSTM-Human-Activity-Recognition) | 840 | Human activity recognition using TensorFlow on smartphone sensors dataset and an LSTM RNN. Classifying the type of movement amongst six categories. |
| [Veles](https://github.com/samsung/veles) | 760 | Distributed machine learning platform (Python, CUDA, OpenCL)
| [Deep Detect](https://github.com/beniz/deepdetect) | 759 | Deep Learning API and Server in C++11 with Python bindings and support for Caffe.
| [TensorFlow DeepQ](https://github.com/nivwusquorum/tensorflow-deepq) | 759 | A deep Q learning demonstration using Google Tensorflow.
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