Housing Prices Competition for Kaggle Learn Users

About this opportunity

This is Kaggle's 'Getting Started' competition for people who have just finished a machine learning course. You predict house sale prices in Ames, Iowa from 79 explanatory variables, and submissions are scored on RMSE between the log of predicted and actual prices. It runs indefinitely with a rolling leaderboard, so there is no deadline and no pressure: you can enter today, improve your score over weeks, and practise feature engineering and regression techniques like random forests and gradient boosting. Kaggle's own Machine Learning course on Kaggle Learn is designed to prepare you for it, and the competition's Code tab is full of public notebooks you can read and learn from. Worth being clear about what it is: a Knowledge competition. There is no cash prize and it awards no points or medals — the value is a real, explainable project and a leaderboard score you can point to.

What you get

• A complete, explainable portfolio project with a public leaderboard score
• Practice in feature engineering and regression (random forests, gradient boosting)
• Hundreds of public notebooks and an active discussion forum to learn from
• Team-up option if you want to work with someone else

Prize or recognition

Knowledge only — no cash prize, and it awards no Kaggle points or medals

Who can take part

Open to anyone with a Kaggle account. Kaggle describes it as being for people with some Python or R and machine-learning basics, especially those who have just completed an online ML course.

Eligibility is copied from the organizer's own published rules — they make the final call. Confirm on the official page before you apply.

Coming later: attendees who leave genuinely useful reviews will earn credits toward paid opportunities. Nothing is being awarded yet — reviews are unpaid and unverified for now.