The article discusses how machine learning techniques are used to predict stock market prices. By combining different methods like Support Vector Regression and Random Forest Regression, researchers aim to create an accurate forecasting model. Stock prices can be influenced by various factors like market volatility and economic conditions, making prediction challenging. The study focuses on developing a model that can provide the best forecast for stock prices, helping investors make informed decisions and potentially earn profits.