Stock Price Prediction Using Machine Learning

This study evaluates the effectiveness of machine learning algorithms in predicting the stock market. Four models are used, with deep learning outperforming others. Support vector regression is ranked second in less error-prone techniques. The study aims to improve stock price prediction for retail investors using advanced machine learning algorithms like Keras Deep Neural Networks, LSTM, and linear regression. The ensemble model, which combines timeseries and deep learning models, offers substantial increases in prediction accuracy, making it a solid solution for retail investors