Kaggle Twitter US Airline Sentiment, Implementation of a Tweet Text Sentiment Analysis Model, using custom trained Word Embeddings and LSTM-Deep learning [TUM-Data Analysis&ML summer 2021] @adrianbruenger @stefanrmmr

Text Sentiment Dashboard created using Stream-lit and deployed using Heroku.

Sentiment Analysis: Given a data of US Airline tweets and their sentiment. The task is to do sentiment analysis about the problems of each major U.S. airline. Twitter data was scraped from February of 2015 and contributors were asked to first classify positive, negative, and neutral tweets, followed by categorizing negative reasons (such as "lat…

Sentiment-Analysis using RNN LSTM ULMFiT

NLP Sentiment Analysis with Naïve Bayes Classifier built in Python without using any libraries.

Processing structured data project - 2nd semester

Analyzing and predicting the sentiment of tweets for different US airlines using ML and DL techniques

This code is used to perform sentiment analysis on US Airline using the Twitter dataset. It uses the CNN model and the LSTM model. You can download this dataset at https://www.kaggle.com/crowdflower/twitter-airline-sentiment.

Streamlit Dashboard to analyze the sentiments of Tweets about US Airlines