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.