Safe Dining

Finds safe dining places in your neighborhood

Transcript

1. Ahmad Haider Insight Data Science 2016
2. 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
3. Makes Real-Time Recommendations for Safety Ratings Restaurants in a Neighborhood SafeDining app
4. 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
5. Workflow Crime dataset Yelp API Preprocessing Defining classification problem Feature Engineering Choosing a model Validation 10-fold cross validation Cross entropy loss measure
6. ™ 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
7. Theft Residential Burglary Robbery Assault Source: mylocalcrime.com Validation My analysis mylocalcrime.com
8. •  Ahmad Haider •  PhD thesis: “Measurement of energy landscapes of biological interactions using Boltzmann sampling” •  Georgia Tech •  Love hiking About Me