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INTERNATIONAL JOURNAL OF CREATIVE RESEARCH THOUGHTS - IJCRT (IJCRT.ORG)
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ISSN Approved Journal No: 2320-2882 | Impact factor: 7.97 | ESTD Year: 2013
Call For Paper - Volume 12 | Issue 7 | Month- July 2024
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Paper Title
ENHANCING STOCK MARKET PREDICTION USING MACHINE LEARNING
Authors
Akhilesh Bhagat, Prathmesh Bhalerao, Roshan Mahajan, Rishikesh Raut, Swapnali Bhujbal
Keywords
Stock Prediction , Data Analysis, Neural Language Processing, Machine Learning.
Abstract
Stock Market Prediction Using Machine Learning is a research area that leverages various data-driven techniques to forecast stock prices and trends. This study explores the application of machine learning algorithms, such as neural networks, decision trees, and support vector machines, to analyze historical stock market data. By training these models on past price movements, trading volumes, and other relevant factors, it aims to predict future stock prices and market trends. The research focuses on evaluating the performance of these algorithms and their potential for providing valuable insights to investors and traders. Ultimately, the goal is to improve the accuracy of stock market predictions, enhancing decision-making in the financial markets.
IJCRT's Publication Details
Unique Identification Number - IJCRT2311311
Paper ID - 246399
Page Number(s) - c647-c654
Pubished in - Volume 11 | Issue 11 | November 2023
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Publisher Name - IJCRT | www.ijcrt.org | ISSN : 2320-2882
E-ISSN Number - 2320-2882
Cite this article
Akhilesh Bhagat, Prathmesh Bhalerao, Roshan Mahajan, Rishikesh Raut, Swapnali Bhujbal, "ENHANCING STOCK MARKET PREDICTION USING MACHINE LEARNING", International Journal of Creative Research Thoughts (IJCRT), ISSN:2320-2882, Volume.11, Issue 11, pp.c647-c654, November 2023, Available at :http://www.ijcrt.org/papers/IJCRT2311311.pdf
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Volume 12 | Issue 7
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Submit Manuscript Online Impact Factor: 7.97 Review Results : Within 02-03 Days Paper Publication : Within 02-03 Days
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ISSN: 2320-2882 Impact Factor: 7.97 and ISSN APPROVED Journal Starting Year (ESTD) : 2013
ISSN and 7.97 Impact Factor Details
ISSN: 2320-2882 Impact Factor: 7.97 and ISSN APPROVED Journal Starting Year (ESTD) : 2013
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