Stock Closing Price Forecasting Using Machine Learning for Prediction and Company Growth

Abstract - With the widespread availability of internet access, participation in the stock market has become increasingly accessible, enabling individuals from diverse backgrounds to engage in trading and investment activities. This project aims to harness the power of machine learning techniques to forecast stock prices, thereby facilitating informed decision-making for company growth and investment strategies. By leveraging historical stock data and employing predictive models, the project seeks to enhance the accuracy and reliability of predicting future stock movements. Through rigorous analysis of historical trends and patterns, the project aims to provide valuable insights that can inform strategic planning and investment decisions in the dynamic financial markets. Ultimately, the project endeavors to empower stakeholders with actionable intelligence derived from advanced machine learning methodologies, thereby contributing to informed decision-making and fostering growth in the stock market landscape.