Abstract
Researchers have been investigating various approaches to accurately forecast stock market prices. Trading professionals can gain better insights regarding data, such as potential trends, by using useful prediction tools. Additionally, since the study predicts future market conditions, investors stand to gain significantly. Using machine learning algorithms for predicting is one such approach. The goal of this study is to increase the accuracy of stock market predictions made using stock valuation. Many academics have developed various approaches to address this issue, primarily using conventional approaches up to this point, like artificial neural networks, which are ways to identify hidden patterns in data and classify it for use in stock market prediction. This initiative suggests a fresh approach to stock forecasting
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