Project Name | Stars | Downloads | Repos Using This | Packages Using This | Most Recent Commit | Total Releases | Latest Release | Open Issues | License | Language |
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Keras Resources | 3,174 | a year ago | 13 | |||||||
Directory of tutorials and open-source code repositories for working with Keras, the Python deep learning library | ||||||||||
Lstm Human Activity Recognition | 3,074 | 2 years ago | 19 | mit | Jupyter Notebook | |||||
Human Activity Recognition example using TensorFlow on smartphone sensors dataset and an LSTM RNN. Classifying the type of movement amongst six activity categories - Guillaume Chevalier | ||||||||||
Twitter Sentiment Analysis | 1,322 | a year ago | 20 | mit | Python | |||||
Sentiment analysis on tweets using Naive Bayes, SVM, CNN, LSTM, etc. | ||||||||||
Vad | 632 | 3 years ago | 32 | MATLAB | ||||||
Voice activity detection (VAD) toolkit including DNN, bDNN, LSTM and ACAM based VAD. We also provide our directly recorded dataset. | ||||||||||
Multilabel Timeseries Classification With Lstm | 487 | 7 years ago | 3 | apache-2.0 | Jupyter Notebook | |||||
Tensorflow implementation of paper: Learning to Diagnose with LSTM Recurrent Neural Networks. | ||||||||||
Attention Networks For Classification | 477 | 4 years ago | 8 | Jupyter Notebook | ||||||
Hierarchical Attention Networks for Document Classification in PyTorch | ||||||||||
Lstm Fcn | 388 | 5 years ago | 7 | Python | ||||||
Codebase for the paper LSTM Fully Convolutional Networks for Time Series Classification | ||||||||||
Cnn_lstm_ctc_tensorflow | 330 | 6 years ago | 26 | mit | Python | |||||
CNN+LSTM+CTC based OCR implemented using tensorflow. | ||||||||||
Handwriting Generation | 289 | 6 years ago | 9 | mit | Python | |||||
Implementation of handwriting generation with use of recurrent neural networks in tensorflow. Based on Alex Graves paper (https://arxiv.org/abs/1308.0850). | ||||||||||
Har Stacked Residual Bidir Lstms | 283 | 2 years ago | 3 | apache-2.0 | Python | |||||
Using deep stacked residual bidirectional LSTM cells (RNN) with TensorFlow, we do Human Activity Recognition (HAR). Classifying the type of movement amongst 6 categories or 18 categories on 2 different datasets. |