# Context
This is homework 1 of the course 'Become a Kaggle Master'.
This course is part of the <a href="https://dauphine.psl.eu/en/training/masters-degrees/computer-science/m2-artificial-intelligence-systems-data">IASD Master 2 in Machine Learning, Artificial Intelligence, and Data Science</a> program, jointly run by <a href="https://dauphine.psl.eu/en/">Université Paris Dauphine</a>, <a href="https://www.ens.psl.eu/en"> ENS</a>  and <a href="https://mines-paristech.eu/"> Mines ParisTech</a>.

# Goal
The goal of the competition is to predict house prices using a modified version of the Ames Housing dataset, which includes 79 features describing various aspects of residential homes. The objective is to develop a model that can accurately predict house prices based on the provided features. The competition is open to all students enrolled in the course and serves as an introduction to Kaggle and practical machine learning