Michael-Pytel/US-Airlines-Analysis

Processing structured data project - 2nd semester

Language: R - Size: 17.3 MB - Last synced at: 4 months ago - Pushed at: 4 months ago - Stars: 0 - Forks: 0

stefanrmmr/kaggle_twitter_airline_sentiment

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

Language: Python - Size: 187 MB - Last synced at: over 1 year ago - Pushed at: almost 2 years ago - Stars: 4 - Forks: 2

sandeepbansode/Support_Vector_Machine_U.S._Airline_tweets_Sentiment_Analysis

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 "late flight" or "rude service").

Language: Jupyter Notebook - Size: 806 KB - Last synced at: over 1 year ago - Pushed at: almost 2 years ago - Stars: 2 - Forks: 0

shreyagopal/US-Airlines-Sentiment-Classification

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

Language: Jupyter Notebook - Size: 2.36 MB - Last synced at: over 1 year ago - Pushed at: over 3 years ago - Stars: 1 - Forks: 3

avinashhsinghh/Sentiment-Analysis-using-RNN-_-LSTM-ULMFiT-

Sentiment-Analysis using RNN LSTM ULMFiT

Language: Jupyter Notebook - Size: 209 KB - Last synced at: over 1 year ago - Pushed at: almost 5 years ago - Stars: 1 - Forks: 0

Euno257/Sentimental-Analysis-on-Twitter-US-Airline-dataset

Language: Jupyter Notebook - Size: 1.84 MB - Last synced at: over 1 year ago - Pushed at: about 5 years ago - Stars: 0 - Forks: 0