| bentrevett/pytorch-sentiment-analysis |
4,133 |
|
0 |
0 |
about 2 years ago |
0 |
|
3 |
mit |
Jupyter Notebook |
| Tutorials on getting started with PyTorch and TorchText for sentiment analysis. |
| guillaumegenthial/sequence_tagging |
1,725 |
|
0 |
0 |
almost 7 years ago |
0 |
|
15 |
apache-2.0 |
Python |
| Named Entity Recognition (LSTM + CRF) - Tensorflow |
| lilianweng/stock-rnn |
1,339 |
|
0 |
0 |
about 4 years ago |
0 |
|
20 |
|
Python |
| Predict stock market prices using RNN model with multilayer LSTM cells + optional multi-stock embeddings. |
| dhwajraj/deep-siamese-text-similarity |
1,216 |
|
0 |
0 |
almost 6 years ago |
0 |
|
29 |
mit |
Python |
| Tensorflow based implementation of deep siamese LSTM network to capture phrase/sentence similarity using character/word embeddings |
| jiesutd/LatticeLSTM |
1,018 |
|
0 |
0 |
almost 7 years ago |
0 |
|
4 |
|
Python |
| Chinese NER using Lattice LSTM. Code for ACL 2018 paper. |
| jiegzhan/multi-class-text-classification-cnn-rnn |
554 |
|
0 |
0 |
about 8 years ago |
0 |
|
29 |
apache-2.0 |
Python |
| Classify Kaggle San Francisco Crime Description into 39 classes. Build the model with CNN, RNN (GRU and LSTM) and Word Embeddings on Tensorflow. |
| monikkinom/ner-lstm |
528 |
|
0 |
0 |
about 7 years ago |
0 |
|
12 |
|
Python |
| Named Entity Recognition using multilayered bidirectional LSTM |
| ShannonAI/glyce |
387 |
|
0 |
0 |
over 3 years ago |
0 |
|
30 |
apache-2.0 |
Python |
| Code for NeurIPS 2019 - Glyce: Glyph-vectors for Chinese Character Representations |
| SenticNet/personality-detection |
273 |
|
0 |
0 |
about 6 years ago |
0 |
|
21 |
mit |
Python |
| Implementation of a hierarchical CNN based model to detect Big Five personality traits |
| Smerity/keras_snli |
265 |
|
0 |
0 |
about 9 years ago |
0 |
|
4 |
mit |
Python |
| Simple Keras model that tackles the Stanford Natural Language Inference (SNLI) corpus using summation and/or recurrent neural networks |
