In the early 1970s, if you wanted to purchase a stock, you would need to engage a broker who would charge you a fixed commission of nearly 1%. If you wanted to purchase an airline ticket, you would need to contact a travel agent who would earn a commission of around 7%. If you wanted to sell a home, you would contact a real estate agent who would earn a commission of 6%. In 2016, you can do the first two essentially for free. The last one remains as it was in the 1970s.

Why is this the case, and more importantly, what does any of this have to do with machine learning? The reality is, it all comes down to data and who has access to it.

You might assume that you can access troves of real estate listing data quite easily through APIs or by web-scraping real estate websites. You would be wrong. Well, wrong if you intend to follow the terms and conditions of these sites. Real estate data is tightly controlled by the National Association of Realtors (NAR) who...