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

Baidu's open-source Sentiment Analysis System.

Text classification using deep learning models in Pytorch

Repository with all what is necessary for sentiment analysis and related areas

텐서플로우와 머신러닝으로 시작하는 자연어처리(로지스틱회귀부터 트랜스포머 챗봇까지)

Archived - not answering issues

An implementation in TensorFlow of a convolutional neural network (CNN) to perform sentiment classification on tweets.

Implementations for a family of attention mechanisms, suitable for all kinds of natural language processing tasks and compatible with TensorFlow 2.0 and Keras.

Attention-based multimodal fusion for sentiment analysis

ConText v4: Neural networks for text categorization

Keras Implementation of Aspect based Sentiment Analysis

My solution to the Natural Language Processing course made by Dan Jurafsky, Chris Manning in Winter 2012

IPython Notebook for training a word-level Convolutional Neural Network model for sentiment classification task on Yelp-Challenge-2016 review dataset.

Pytorch implementation of Sentiment Classification in Improved Semantic Representations From Tree-Structured Long Short-Term Memory Networks

Text classification with Convolution Neural Networks on Yelp, IMDB & sentence polarity dataset v1.0

LSTM and CNN sentiment analysis

Your Advanced Twitter stalking tool

Machine Learning (EE 5184) in NTU

Automate swing trading using deep reinforcement learning. The deep deterministic policy gradient-based neural network model trains to choose an action to sell, buy, or hold the stocks to maximize the gain in asset value. The paper also acknowledges the need for a system that predicts the trend in stock value to work along with the reinforcement learning algorithm. We implement a sentiment analysis model using a recurrent convolutional neural network to predict the stock trend from the financial news. The objective of this paper is not to build a better trading bot, but to prove that reinforcement learning is capable of learning the tricks of stock trading.

Accurate and fast sentiment scoring of phrases with #hashtags, emoticons :) & emojis 🎉

🎤 Lyrics/associated NLP data for Billboard's Top 100, 1950-2015.

A dataset contains 37 million douban dushu comments

【仅作为交流学习使用】机器智能--相关书目及经典论文包括AutoML、情感分类、语音识别、声纹识别、语音合成实验代码等

Hierarchical Attention Networks for Document Classification in Keras

Augmento sentiment data quickstart and research

Recurrent neural networks and Dynamic memory networks for sentiment classification

Twitter Bot to follow financial trends in publicly traded companies