Stock Market Predicition using Sentiment Analysis

Project Details

Domain : Machine Learning
Completed On : January 2019 - April 2019

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Performed Web Scrapping to collect NEWS and Twitter data using 'Beautiful Soup' and 'Tweepy'.

Parsed this data to NLTK's sentiment intensity analyzer tool to get the sentiment score and combined this data with the closing stock price collected using API of 'WorldTradingData'.

'Artificial Neural Network' and 'Long/Short Term Memory'(LSTM) were implemented to train a model using Keras Library.

Genetic Algorithm was incorporated with LSTM to find the best weights, bias parameters and reduce RMSE value of the model.