This repo has detailed explanation of linear regression over sample data with one predictor.

Covers

• Visualization of data using seaborn
• Simple linear regression implementation using normal equations (using Numpy)
• Gradient descent optimization (using numpy)
• R-squared implementation using numpy
• Residual plot analysis
• Comparison of model using normal equation with scikit implementation

Concepts are inspired from Prof. Andrew Ng's machine learning course and Siraj Raval's Videos.