Stock Prediction Analysis by using Linear Regression Machine Learning Algorithm
Sankranti Srinivasa Rao
Sankranti Srinivasa Rao, Department of EECE, GITAM Deemed to be University, Visakhapatnam, India.
Manuscript received on January 13, 2020. | Revised Manuscript received on January 22, 2020. | Manuscript published on February 10, 2020. | PP: 841-844 | Volume-9 Issue-4, February 2020. | Retrieval Number: D1110029420/2020©BEIESP | DOI: 10.35940/ijitee.D1110.029420
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Stock market is varying day to day. Many factors such as government policies, industry performance, market sentiment etc are the main cause of up and downs in stock market. To invest money in stock market, study and analysis of stock market is essential. This type of analysis can be done by using Machine learning algorithms. The main objective of this paper is to predict the stock market future values by using linear regression machine learn algorithms based on past values. The methodology is developed and implemented in python on APPLE and TSLA stock.
Keywords: Linear Regression, Prediction, Supervised Learning, Stock
Scope of the Article: Machine Learning