Sentiment Analysis Using Bidirectional LSTM
Sentiment Analysis of Tweets with Deep Learning
This is a sentiment analysis project based on Bidirectional LSTM and Natural Language Processing. This project finds more than 90% accuracy while classifying sentiments. The project was done using python, nltk, and numerous libraries. The major libraries used libraries are numpy, pandas, os, tweetpy, re, scikit-learn, tensorflow, keras, seaborn, and matplotlib.
Figure: The results of the Bidirectional LSTM Model
Figure: Bidirectional LSTM Model in action.
The project can be found here