Hey everyone, so today we will be trying to understand how Linear Regression works and how to implement a simple univariate Linear Regression from scratch.
Implement a simple multivariate Linear Regression using Numpy. In the example we showed, we had one X and a corresponding Y for every X. In the case of multivariate regression, there will be multiple features together called X and for each input there is a corresponding output Y. Link to Dataset
The Dataset contains 4 features and the corresponding output. Implement a simple Linear Regresion utilising all these 4 features by associating a corresponding variable for each to map them to the output variables.
Implementing from scratch link