Stock Market Prediction and Education Platform Using Machine Learning

Abstract

The ability to predict stock market trends accurately is highly valuable for investors and traders. This paper presents an integrated machine learning-based system that predicts stock prices using historical data and news sentiment analysis. The platform leverages techniques like sentiment analysis, Named Entity Recognition (NER), and deep learning models such as Bidirectional Long Short-Term Memory (Bi-LSTM). Along with predictions, the platform offers educational resources to enhance financial literacy, making it an ideal tool for novice investors seeking both knowledge and actionable market insights.