The aim of this project is to perform sentiment analysis on Airbnb Data using a neutral network model, Long Short-Term Memory. Dataset was colelcted from Kagle in the form of csv file. The dataset was raw and preprocessing was required to clean the data before feeding it to the LSTM.
Some of the pre-processing steps include : Tokenizing, POS tag, Word2Vec, Normalizing and the output prediction obtained from LSTM is 75%.