Analysis on the different methods of implementing Linear Regression
The project analyses the different methods of implementing Linear Regression: Least Squared with Normal Equations, Batch Gradient Descent and Stochastic Gradient Descent. Based on the Mean Squared Error metric, results are compared to the method implemented in the SKLearn module.