Authors : Gaurav Solanki; Bibek Kumar Jha; Yash Anand; Pritam Kumar Rout; Piyush Mandal

Volume/Issue : Volume 10 - 2025, Issue 4 - April

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Google Scholar : https://tinyurl.com/y2kxecc3

Scribd : https://tinyurl.com/2zyste5v

DOI : https://doi.org/10.38124/ijisrt/25apr1288

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Abstract : This project is focused on creating a machine learning model to predict stock market prices by examining past data and market indicators. We apply regression and deep learning techniques to improve prediction accuracy. The main goal is to aid stock market analysis with a dashboard developed using the LSTM (Long Short-Term Memory) model. We will explain how the model functions and show how it can be used for making real-time predictions. We'll also talk about the challenges faced during its development. LSTM models are excellent for analyzing data that changes over time and for spotting long-term trends. They are especially useful for predicting time series, such as stock prices, because they can adapt to new market data rather than depending on fixed rules.

Keywords : Forecast, Precision, Market Signals.

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