Predicting Stock Market Trends Using Machine Learning Algorithms

The stock market is inherently dynamic and uncertain, making its prediction a challenging task due to constant fluctuations and instability. The primary objective of this study is to analyze and predict future market trends with greater accuracy and reliability. Over the years, numerous researchers have investigated stock market behavior to understand its evolution and improve forecasting methods. Since stock data is highly volatile, it serves as a critical source for evaluating prediction efficiency, where even small variations can significantly influence outcomes.In recent years, machine learning has emerged as a powerful tool in stock market prediction, offering advanced techniques for handling large datasets and building reliable predictive models. By leveraging machine learning algorithms, particularly regression-based approaches, this research aims to predict stock values with improved precision. The proposed work emphasizes the integration of machine learning regression techniques to enhance decision-making in financial forecasting.