Predicted house prices using multiple linear regression. Used back elimination to further improve the model and select features based on p-value and adjusted R squared value.
Regression is one of the foundational techniques in Machine Learning. Being one of the most well-understood algorithms, beginners always struggle to understand some fundamental terminology related to regression. In this series of projects, I will try to give you basic ideas of underlying concepts with the help of practical examples. If you are starting your career or want to brush up on your knowledge of regression, this repo is made up for you. These projects begins by introducing some simple real-life examples for regression. From a brief introduction to most of the concepts used in regression to hands-on experience, these projects will give you enough understanding to apply those in real-world problems. With the help of the background developed, you will code your regression model in python.