Housing Prices Competition for Kaggle Learn Users

Overview

This competition is designed for users who have completed Kaggle Learn's Machine Learning course and want to practice their skills. You'll work with a dataset of homes in Ames, Iowa, with 79 features, and your goal is to predict the final sale price of each house. It's a great way to apply regression techniques and feature engineering.

Requirements

Teams can be formed, or you can participate individually. This competition is recommended for those with basic R or Python and machine learning knowledge. You'll submit your predictions in a CSV file with 'Id' and 'SalePrice' columns. The evaluation metric is the logarithm of the predicted sale price compared to the observed sale price.

Prizes

This is a 'Getting Started' competition, so there are no cash prizes or medals. The primary benefit is the practical experience gained in applying machine learning and regression techniques to a real-world dataset.