Stock Market Price Prediction Using Machine Learning

Because the stock market is always changing and unpredictable, predicting its price is a difficult job.The tools of machine learning (ML) have become popular in the effort to understand trends in the stockmarket. The report examines how ML is used to forecast stock prices using older data, featuredevelopment and model advances. A number of algorithms such as regression, support vector machines,decision trees and neural networks, are tested to see how accurately they predict results. Evaluationmetrics such as mean squared error, root mean squared error and correlation coefficient are used to chequetheir performance. Data visualisation is also used to help find out the common trends found among thevarious markets. Results indicate that ML models are able to give accurate predictions which depends ondata, the features selected and the algorithm chosen. It argues that with ML, investors and traders getvaluable insights which support them to make better decisions in the markets.