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Multiple Linear Regression

This project predicts house prices using machine learning models based on the King County House Sales dataset. It explores Simple Linear, Multiple Linear, Polynomial, and Ridge Regression models, comparing their performance in terms of accuracy. The best model identified is Polynomial Regression, achieving an R² score of 0.75.

A Python module, primarily on linear and multiple regression including normalizing data, computing hypothesis, and evaluating cost.

Multiple Regression is almost like Simple Linear Regression, but with more than a single independent feature, which means we try to predict a value based on more than one variable.

check this project article on medium: https://medium.com/@alhendyrenad/build-a-multiple-linear-regression-model-using-python-c4d9f9cf4cc7