Stock Market Price Prediction and Analysis

This project involved analyzing historical stock market data to predict stock price trends using machine learning techniques. I utilized Python libraries such as pandas, numpy, and matplotlib for data preprocessing and visualization, and implemented regression models to forecast stock prices. The project demonstrated how data science can empower investors with data-driven insights to make informed financial decisions. Key features included trend analysis, predictive modeling, and interactive visualizations.