Welcome to the Linear Regression Repository! This project demonstrates the implementation of linear regression, a foundational machine learning algorithm used for predicting continuous values based on input data.

Features Linear Regression Implementation: A step-by-step approach to building a linear regression model. Gradient Descent Optimization: Learn how gradient descent improves model performance. Data Preprocessing: Techniques for handling missing values, scaling, and splitting datasets. Evaluation Metrics: Mean Squared Error (MSE), Mean Absolute Error (MAE), and R-squared score calculations. Visualization: Plotting regression lines and data points for better understanding.