INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT International Peer Reviewed & Refereed Journals, Open Access Journal ISSN Approved Journal No: 2456-4184 | Impact factor: 8.76 | ESTD Year: 2016
Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.76 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI)
In this paper, we have developed a stock data predictor programme that uses prior stock prices and data as training sets to predict specific shares stock prices.
In this paper, the suggested LSTM model's implementation in Python uses past data to forecast the price of Maruti Suzuki Motars's stock in the future. The visualisation of the Maruti Suzuki Share prediction is shown. The creation of an algorithm that forecasts the share price of a company for a specific time period is the subject of our study.
The suggested approach can predict the share price with a very low loss and error rate; however, the training will be more effective if the epoch batch size is increased.
Keywords:
Machine Learning, Stock Price Prediction, Long ShortTerm Memory, Stock Market, National Stock Exchange
Cite Article:
"Stock Price Prediction Using LSTM", International Journal of Novel Research and Development (www.ijnrd.org), ISSN:2456-4184, Vol.8, Issue 7, page no.b755-b760, July-2023, Available :http://www.ijnrd.org/papers/IJNRD2307185.pdf
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ISSN:
2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar| ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.76 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
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