Welcome to the Apartment Price Prediction Competition!

In this competition, participants are tasked with building a machine learning model to predict the price of apartments based on various features such as the number of rooms, the district, building structure type, and more. The dataset includes information on 11,884 apartments, each with multiple characteristics that influence its price.

Goal

The goal is to create a model that can accurately predict the price of apartments based on the provided features. Participants will compete to develop the most effective model for this task, using any techniques or algorithms they prefer.

The winning models will be those that most accurately predict the apartment prices on the test set.

You can submit your predictions and see how your model performs on the leaderboard. Don’t forget to review the Kaggle competition documentation for guidance on how to participate.

Good luck, and happy modeling!

Feel free to adjust any part of this to better fit your vision for the competition!