| axa-group/nlp.js |
5,944 |
|
1 |
92 |
over 2 years ago |
40 |
January 12, 2023 |
109 |
mit |
JavaScript |
| An NLP library for building bots, with entity extraction, sentiment analysis, automatic language identify, and so more |
| 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. |
| thisandagain/sentiment |
2,208 |
|
980 |
117 |
almost 6 years ago |
26 |
August 22, 2019 |
14 |
mit |
JavaScript |
| AFINN-based sentiment analysis for Node.js. |
| songyouwei/ABSA-PyTorch |
1,782 |
|
0 |
0 |
almost 3 years ago |
0 |
|
91 |
mit |
Python |
| Aspect Based Sentiment Analysis, PyTorch Implementations. 基于方面的情感分析，使用PyTorch实现。 |
| shirosaidev/stocksight |
1,557 |
|
0 |
0 |
over 3 years ago |
0 |
|
8 |
apache-2.0 |
Python |
| Stock market analyzer and predictor using Elasticsearch, Twitter, News headlines and Python natural language processing and sentiment analysis |
| 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. |
| baidu/Senta |
1,272 |
|
0 |
0 |
almost 5 years ago |
6 |
May 21, 2020 |
50 |
apache-2.0 |
Python |
| Baidu's open-source Sentiment Analysis System. |
| dipanjanS/text-analytics-with-python |
1,073 |
|
0 |
0 |
over 5 years ago |
0 |
|
0 |
apache-2.0 |
Jupyter Notebook |
| Learn how to process, classify, cluster, summarize, understand syntax, semantics and sentiment of text data with the power of Python! This repository contains code and datasets used in my book, "Text Analytics with Python" published by Apress/Springer. |
| winkjs/wink-nlp |
1,057 |
|
0 |
12 |
over 2 years ago |
33 |
July 21, 2023 |
0 |
mit |
JavaScript |
| Developer friendly Natural Language Processing ✨ |
| curiousily/Getting-Things-Done-with-Pytorch |
873 |
|
0 |
0 |
almost 5 years ago |
0 |
|
13 |
apache-2.0 |
Jupyter Notebook |
| Jupyter Notebook tutorials on solving real-world problems with Machine Learning & Deep Learning using PyTorch. Topics: Face detection with Detectron 2, Time Series anomaly detection with LSTM Autoencoders, Object Detection with YOLO v5, Build your first Neural Network, Time Series forecasting for Coronavirus daily cases, Sentiment Analysis with BERT. |
