An Introduction to the Property Pricing Data Science Project

Getting a dang hold of this dang housing market

To put it in brief, this project is the child of idle hands and frustration. I have been looking at the housing market for a while and the only thing I have found out is that I don't know crap about it and nobody around me has any clue how it's actually going to develop nor what's a good property to buy.

So I figured, let's go ask someone or something smarter, after which I looked up some experts in the field and found out what they thought, and they didn't seem to be aligned either.

Therefore I decided that it was time to pick up the task myself, and hand it over to a computer.. or rather.. a machine.

Enough foreshadowing; this project is a machine learning project where me and my friend tries to solve our problem of not understanding the housing market as a whole nor the individual listings.

And like any other diligent data science engineer (I hope this isn't a protected title) my friend and I etched out the challenges that was lying ahead of us:

  1. Get some dang data
  2. Transform the dang data
  3. Pop the dang data into a modul and train it
  4. Figure out something dang interesting

Getting some dang data

We couldn't find any public sources that had listing data

  1. We So essentially there's a few elements for this process: !insertgraphics

.... to be done ...