Stock Price Prediction using Machine Learning

This project focuses on predicting stock prices using machine learning techniques and historical financial data.

The workflow includes:

- Data collection and preprocessing

- Feature engineering (time-based features)

- Exploratory data analysis (EDA)

- Regression modeling for price prediction

- Model evaluation using R² and MSE

Tools & Technologies:

Python, Pandas, NumPy, Scikit-learn, Matplotlib

Key Results:

- Accurate prediction of stock price trends

- Strong regression performance

- Clear visualization of predicted vs actual values

This project highlights my ability to work with time-series data and build predictive models for financial analysis.