Abstract: 

"In this talk we will use the housing crisis using data from the Kansas City Housing Authority to explore Kansas City eviction trends and patterns in the past 2 decades. We will be using census data containing financials and demographics to determine eviction trends and model eviction probability. In particular, we'll explore:
- What features makes someone likely to be evicted?
- Who are the ones performing these evictions?
- Do these trends change over time? If so, in which ways?

We will cover the entire process, from getting the raw data, cleaning and integrating the different sources, and building visualizations using several tools:
- Python
- SQL + PostGIS
- Spark
- Dataiku Data Science Studio
"

Bio: 

Henri Dwyer is a data scientist and engineer working on building the best platform for data scientists at Dataiku. Before, he worked in physics research, on air pollution and solar cells. He has built projects in a variety of industries ranging from marketing, pharmaceutical industry and transportation.