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Research Paper | Computer Science | Volume 15 Issue 8, August 2026 | Pages: 1859 - 1860 | India
AI-Powered Stock Price Prediction System Using Machine Learning
Abstract: The stock price prediction is difficult owing to the dynamic, volatile and non-linear nature of the financial markets. Proper forecasting will help users make good decisions. This study focuses on the AI-Powered Stock Price Prediction System Using Machine Learning, which uses Linear Regression and Random Forest Regression on past data of the stock market. The proposed system comprises data collection, data preprocessing, feature selection, model training, prediction, and model performance assessment. Linear Regression model is used as a baseline model to find the linear pattern of the data whereas Random Forest Regression finds the nonlinear patterns of the data. The performance of both models is assessed based on the following metrics: Mean Absolute Error (MAE), Mean Squared Error (MSE), Root Mean Squared Error (RMSE), and R? Score. The findings of this experiment reveal that the prediction accuracy of the Random Forest Regression is higher than Linear Regression. The proposed system will help users to analyse past trends and make informed decisions.
Keywords: Stock Price Prediction, Linear Regression, Random Forest Regression, Financial Forecasting, Historical Stock Data, Predictive Analytics, Data Preprocessing
How to Cite?: Pavani K J, Akhila S Babu, "AI-Powered Stock Price Prediction System Using Machine Learning", Volume 15 Issue 8, August 2026, International Journal of Science and Research (IJSR), Pages: 1859-1860, https://www.ijsr.net/getabstract.php?paperid=MR26825115250, DOI: https://dx.doi.org/10.21275/MR26825115250