RealDeal focuses on acquiring and selling houses/apartments in Rotterdam, taking advantage of market fluctuations. In some cases RealDeal adds value by making renovations to the property before listing them for sale, in other cases they simply identify good opportunities and perform a quick sell at a profit.

As a first step towards a complete solution, you decide to assess how easy it is to predict house prices as a function of some of their publicly available characteristics. This task will provide you with some information on the likelihood that you can develop a good solution for RealDeal. You decide do scrape a real estate web site (https://www.funda.nl) and gather information about all properties available for sale in Rotterdam. After some data cleaning you assemble a data set with information that may (or may not) be useful to predict the listing price of a property, including location (zipcode), area, amenities, along with other information.

You should run the models you believe are adequate and that you believe will provide the best predictions. You can use the knowledge acquired in the individual assignment as starting point for this task. This task is different from the task in individual assignment in at least one important aspect. This is not a classification task. Your goal is to predict prices (a continuous variable), and not whether an instance belongs to a specific class.