This document discusses using Bayesian analysis and probabilistic modeling to build a tool that analyzes Craigslist housing listings data. It extracts key information like price and location from listings to develop likelihood and prior probability distributions. The goal is to predict the probability of finding a particular price given a location based on the data, using techniques like Gaussian and box car distributions to model the likelihood and prior respectively. The tool would filter out spam and noise words to provide more useful results for users searching housing listings.

1. Craigslist ++
Sara Salha
Insight Data science Fellow

3. Likelihood of finding a particular
price, at a given location
$ 900
$ 3900

4. Probabilistic Model
Bayesian analysis
Probability (Price (location) | Data)
Likelihood(Data | Price(location)) x
Prior (Price(location))
Likelihood ~ Gaussian distribution
Prior ~ box car

5. Tools
Room Share Student ASAP roommate
House family pool apply ...
Spam $ 1 free models ethnicity
Noise
less
quiet serene focus studying
parking garage street parking parking ...
kitchen full kitchen kitchen cooking ...

6. Tools

7. Sara Salha
Phd Physics, UCLA
Phase Retrieval from Incomplete Noisy Data