Comparative Analysis of Python-Based Machine Learning Algorithms for Stock Market Prediction

It is very difficult to forecast the stock market because of the high volatility and unpredictable nature of stock prices. Because of the remarkable advancements in machine learning algorithms over the past ten years, stock market forecasting has gained more attention and developed into one of the most reliable methods for predicting stock movements. The current research project includes a thorough analysis of a few machine learning techniques based on Python for stock market forecasting. Several algorithms' performance will be compared and their ability to predict stock prices will be assessed. The results have demonstrated that the application of machine learning techniques can significantly enhance stock market prediction. Consequently, this review will be helpful to academics and others who may be interested in the use of machine learning in stock market forecasting.