FinGPT: Open-Source Financial Large Language Models! Revolutionize 🔥 We release the trained model on HuggingFace.

👑 Easy-to-use and powerful NLP and LLM library with 🤗 Awesome model zoo, supporting wide-range of NLP tasks from research to industrial applications, including 🗂Text Classification, 🔍 Neural Search, ❓ Question Answering, ℹ️ Information Extraction, 📄 Document Intelligence, 💌 Sentiment Analysis etc.

Web mining module for Python, with tools for scraping, natural language processing, machine learning, network analysis and visualization.

An NLP library for building bots, with entity extraction, sentiment analysis, automatic language identify, and so more

Projects and exercises for the latest Deep Learning ND program https://www.udacity.com/course/deep-learning-nanodegree--nd101

Tutorials on getting started with PyTorch and TorchText for sentiment analysis.

搜索所有中文NLP数据集，附常用英文NLP数据集

State of the Art Natural Language Processing

Rust native ready-to-use NLP pipelines and transformer-based models (BERT, DistilBERT, GPT2,...)

AFINN-based sentiment analysis for Node.js.

文本挖掘和预处理工具（文本清洗、新词发现、情感分析、实体识别链接、关键词抽取、知识抽取、句法分析等），无监督或弱监督方法

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 BER

Stock market analyzer and predictor using Elasticsearch, Twitter, News headlines and Python natural language processing and sentiment analysis

🐗 🐻 Deep Learning based Python Library for Stock Market Prediction and Modelling

Aspect Based Sentiment Analysis, PyTorch Implementations. 基于方面的情感分析，使用PyTorch实现。

Baidu's open-source Sentiment Analysis System.

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.

Sentiment analysis on tweets using Naive Bayes, SVM, CNN, LSTM, etc.

State-of-the-art deep learning model for analyzing sentiment, emotion, sarcasm etc.

This repo contains implementation of different architectures for emotion recognition in conversations.