Stock Prediction: NLP and Deep Learning Approach

  • Mr. Yogesh Bodkhe, Prof. Rushali A. Deshmukh


People tend to analyze existing strategies and so planned new strategies for inventory prediction. We have used Sentiment evaluation and Technical evaluation through NLP and Deep mastering approach. To take advantage of sentiment analysis on enterprise associated inventory, we have proposed a machine that will use the sentiment analysis on twits associated with special sectors (e.g. IT sector, Banking sector, Pharmaceutical sector, Automobile sector, Infrastructure sector.) which might be extracted from twits. These twits are extracted from twitter for calculating polarity. The rating of sentiment analysis is calculated here by using algorithm. According to the sector, we have taken 20 groups—the top four performer businesses of every sector. Using the polarity score, we will finalize pinnacle ten groups with great sentiment ratings. We will download the CSV facts of historical share charge of the top ten organizations that we have selected. Then downloaded CSV records are used to build a CNN version to predict in addition stock movement of these pinnacle ten companies.