Skip to content
×
PRO
Pro Members Get Full Access!
Get off the sidelines and take action in real estate investing with BiggerPockets Pro. Our comprehensive suite of tools and resources minimize mistakes, support informed decisions, and propel you to success.
Advanced networking features
Market and Deal Finder tools
Property analysis calculators
Landlord Command Center
$0
TODAY
$69.00/month when billed monthly.
$32.50/month when billed annually.
7 day free trial. Cancel anytime
Already a Pro Member? Sign in here

Join Over 3 Million Real Estate Investors

Create a free BiggerPockets account to comment, participate, and connect with over 3 million real estate investors.
Use your real name
By signing up, you indicate that you agree to the BiggerPockets Terms & Conditions.
The community here is like my own little personal real estate army that I can depend upon to help me through ANY problems I come across.
Real Estate Technology
All Forum Categories
Followed Discussions
Followed Categories
Followed People
Followed Locations
Market News & Data
General Info
Real Estate Strategies
Landlording & Rental Properties
Real Estate Professionals
Financial, Tax, & Legal
Real Estate Classifieds
Reviews & Feedback

Updated over 3 years ago, 08/02/2021

User Stats

13
Posts
12
Votes
Jason Ling
  • Saint Petersburg, FL
12
Votes |
13
Posts

Machine learning and Real Estate Investing

Jason Ling
  • Saint Petersburg, FL
Posted

Big question - why hasn't anyone applied data science and machine learning in the real estate domain?

With the recent (7 years?) advances in natural language processing, image recognition and the validation of various machine learning models why haven't savy investors started a mad race towards developing the ultimate valuation tool?

I've been dabbling in tackling this problem - and so far, it's not that bad.

The only big problems I see is that the data sources for national markets are not uniform.

That the given data might be incomplete or even contain errors (which will affect your model).

That the sample set might be orders of magnitude smaller than your feature space (fixable via removing or combining linearly correlated features to yield an orthogonal feature set)

...So why hasn't anyone done this yet?

Loading replies...