Download - Big data in real estate
BigData in Real estateRAJESH CHILAMANTHULA
Agenda Traditional real estate operation
How BigData is changing Real estate
Challenges
Proposed Analysis
Algorithm & Example
Traditional Real estate operation Contacting Real estate Agents.
Classifieds/other sources.
Pricing comparisons
Final deal.
How BigData Changing Real estate.
"In God we trust, all others bring data.” - William Edwards Deming
BigData
Real estate is next!
Better Understanding of communities
Bankers/investors – mortgaging and foreclosures
How BigData Changing Real estate.
Impact on sales
Ease of finding rentals - Example – Housing.com
Estimates for properties.
Targeted Consumers
Finding agents for advice.
Challenges Collection of Data.
Expiration of listings/Data.
Prediction is not easy!
Other factors like unawareness of neighborhood.
Proposed Analysis New York city Home valuations
New projects in the city
Effect of new developments on the real estate of City
AlgorithmLinear Regression Widely used and well-understood. Runs very fast. Easy to use and minimal tuning. Basis for other machine learning techniques.
Algorithms/technologies used in domain Linear Regression Classification Clustering Neuro lab, Matplotlib, Weka.
Linear Regression - Example
Predicting house values.
Linear Regression - Example f(x) = a + bx
f(x)
x
References http://dataconomy.com/linear-regression-implementation-in-python/ Quora https://
data.cityofnewyork.us/Housing-Development/Projects-in-construction/8586-3zfm
Zillow, Trulia Housing.com http://
realtormag.realtor.org/daily-news/2015/08/07/3-ways-big-data-changing-real-estate
http://mashable.com/2014/07/09/big-data-real-estate/#G0aeozZZS8qE
Queries?