sentiment-classification

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

Baidu's open-source Sentiment Analysis System.

A list of NLP(Natural Language Processing) tutorials

Text classification using deep learning models in Pytorch

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

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

텐서플로우와 머신러닝으로 시작하는 자연어처리(로지스틱회귀부터 트랜스포머 챗봇까지)

Archived - not answering issues

This repository contains the official release of the model "BanglaBERT" and associated downstream finetuning code and datasets introduced in the paper titled "BanglaBERT: Language Model Pretraining and Benchmarks for Low-Resource Language Understanding Evaluation in Bangla" accpeted in Findings of the Annual Conference of the North American Chapter of the Association for Computational Linguistics: NAACL-2022.

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

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

Keras Implementation of Aspect based Sentiment Analysis

ConText v4: Neural networks for text categorization

LSTM and CNN sentiment analysis

Your Advanced Twitter stalking tool

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

This project's aim, is to explore the world of Natural Language Processing (NLP) by building what is known as a Sentiment Analysis Model. We will be implementing and comparing both a Naïve Bayes and a Deep Learning LSTM model.

Get started with Machine Learning with Python - An introduction with Python programming examples

Twitter Bot to follow financial trends in publicly traded companies

Hierarchical Attention Networks for Document Classification in Keras

Machine Learning (EE 5184) in NTU

sentiment analysis、情感分析、文本分类、基于字典、python、classification

Codes for our paper "SentiLARE: Sentiment-Aware Language Representation Learning with Linguistic Knowledge" (EMNLP 2020)

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.

An example project using a feed-forward neural network for text sentiment classification trained with 25,000 movie reviews from the IMDB website.