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ahmad0510
February 16, 2016
Technology
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Safe Dining
Finds safe dining options in your neighborhood
ahmad0510
February 16, 2016
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Transcript
Ahmad Haider Insight Data Science 2016
Personal Story What if I could find which restaurants are
safe and which are not? Mugged @Parking lot ! L Hungry for Pizza! Closest pizza location
Makes Real-Time Recommendations for Safety Ratings Restaurants in a Neighborhood
SafeDining app
I want to eat Pizza at 2+ rated restaurant within
3 miles of my location p1 p2 p3 p4 p5 p1 p2 p3 p4 p1 p2 p1 p2 p3 p4 p5 p6 p7 p8 p1 Crime Location Crime Probability 1. pRest 1. pRest 1. pRest 1. pRest pRest Crime Probability at restaurant pRest pRest pRest pRest pRest pRest pRest 2. Relative Safety Index 2. Relative Safety Index 2. Relative Safety Index 2. Relative Safety Index
Workflow Crime dataset Yelp API Preprocessing Defining classification problem Feature
Engineering Choosing a model Validation 10-fold cross validation Cross entropy loss measure
Multiclass Classification Predict the hour at which crime happens
at given location Features: 35 -- Location (Lat., Long.) , Time (dd, wk, mm, yyyy) Labels: 24 classes (hour of day) Logistic Regression Cross entropy loss measure = 2.95 Algorithm
Theft Residential Burglary Robbery Assault Source: mylocalcrime.com Validation My analysis
mylocalcrime.com
• Ahmad Haider • PhD thesis: “Measurement of energy landscapes
of biological interactions using Boltzmann sampling” • Georgia Tech • Love hiking About Me
None