| fchollet/keras-resources |
3,174 |
|
0 |
0 |
over 3 years ago |
0 |
|
13 |
|
|
| Directory of tutorials and open-source code repositories for working with Keras, the Python deep learning library |
| guillaume-chevalier/LSTM-Human-Activity-Recognition |
3,074 |
|
0 |
0 |
over 3 years ago |
0 |
|
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 |
| abdulfatir/twitter-sentiment-analysis |
1,322 |
|
0 |
0 |
about 3 years ago |
0 |
|
20 |
mit |
Python |
| Sentiment analysis on tweets using Naive Bayes, SVM, CNN, LSTM, etc. |
| jtkim-kaist/VAD |
632 |
|
0 |
0 |
almost 5 years ago |
0 |
|
32 |
|
MATLAB |
| Voice activity detection (VAD) toolkit including DNN, bDNN, LSTM and ACAM based VAD. We also provide our directly recorded dataset. |
| aqibsaeed/Multilabel-timeseries-classification-with-LSTM |
487 |
|
0 |
0 |
almost 9 years ago |
0 |
|
3 |
apache-2.0 |
Jupyter Notebook |
| Tensorflow implementation of paper: Learning to Diagnose with LSTM Recurrent Neural Networks. |
| EdGENetworks/attention-networks-for-classification |
477 |
|
0 |
0 |
about 6 years ago |
0 |
|
8 |
|
Jupyter Notebook |
| Hierarchical Attention Networks for Document Classification in PyTorch |
| titu1994/LSTM-FCN |
388 |
|
0 |
0 |
about 7 years ago |
0 |
|
7 |
|
Python |
| Codebase for the paper LSTM Fully Convolutional Networks for Time Series Classification |
| watsonyanghx/CNN_LSTM_CTC_Tensorflow |
330 |
|
0 |
0 |
almost 8 years ago |
0 |
|
26 |
mit |
Python |
| CNN+LSTM+CTC based OCR implemented using tensorflow. |
| Grzego/handwriting-generation |
289 |
|
0 |
0 |
about 8 years ago |
0 |
|
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). |
| guillaume-chevalier/HAR-stacked-residual-bidir-LSTMs |
283 |
|
0 |
0 |
over 3 years ago |
0 |
|
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. |
