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?