Stock Prediction Application using Machine Learning

The stock market is an exceptionally powerful market where nothing is basically as steady as a stone however as the innovation is overhauling there are numerous ways and strategies one can attempt to realize this powerful change and be arranged appropriately. This paper centers around such various strategies for progressively learning the market and its patterns. We have involved two distinct models for this paper and have additionally performed sentiment analysis on the tweets in regards to the organization or the stock, the model with the least mistake is the ideal and the most favored technique for prediction. The aftereffects of this arrangement have given an unmistakable and shrewd thought regarding the random ups and downs of the market and furthermore another methodology for investors with the goal that they know where they can wager their cash. The ARIMA model is giving the best accuracy for each stock.