# Kaggle Challenge - Exploratory Data Analysis

Our project is based on the Kaggle Housing Prices Competition. In this challenge we are given a dataset with different attributes for houses and their prices. Our goal is to develop a model that can predict the prices of houses based on this data.

At this point we already know two things:

- We are given labeled training examples
- We are asked to predict a value

What do these tell us in terms of framing our problem? The first point tells us that this is clearly a typical **supervised learning** task, while the second one tells us that this is a typical **regression** task.

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