Popular GitHub Repositories for Nlkt

Texts from twitter has been collected to decide the impact, it has been causing the public .We took a testing dataset and used neural network – Model training for testing the retrieved tweets and gain prediction of the sentiments from their tweets.

This a project which predicts the stock price of Tesla for a given time period & based upon the previous 10 years of historical data. Here, numerical and sentimental analysis is performed with the help of natural language toolkit (NLKT), Textblob, sklearn etc. By observing the previous trends of the market stock price and sentiments of the news about the market, this model predicted the future variation of the stock market price of TELSA. Basically, four models were trained with the same dataset like: Random Forest, AdaBoost, LGBM & xgboost out of these model LGBM model predicted with the least mean squared error value.