• Piyush kapse
• Swapnil meshram
• Prafullakumar Jha
• Ketki Bhandarkar
• Anup D. Bhange

The aim of the paper is to examine a number of different forecasting techniques to predict future stock returns based on past returns and numerical news indicators to construct a portfolio of multiple stocks in order to diversify the risk. We do this by applying supervised learning methods for stock price forecasting by interpreting the seemingly chaotic market data. The paper being build is being built to predict the future stock prices for the investor to predict the future stocks, and this is done by the usage of the social medium platform by the use Twitter API. This is being used to calculate the sentiment over the market places and accordingly could be used to predict the prices. The concept being applied could be achieved by using the platform such as python as programming, deep learning for studying the data available of the companies and provide and accuracy and Twitter as a platform to carry the sentiment analysis

Machine learning , Twitter API ,supervised learning, python, sentiment analysis

"Stock market prediction using machine learning and linear regression algorithm ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 2, page no.380-382, February-2019, Available :http://www.jetir.org/papers/JETIR1902758.pdf

"Stock market prediction using machine learning and linear regression algorithm ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 2, page no. pp380-382, February-2019, Available at : http://www.jetir.org/papers/JETIR1902758.pdf