Gimme Shelter: Using Python to Find an Apartment in Toronto
by Ian Whitestone
With a continued shortage of rental units, finding the ideal apartment in Toronto, let alone one you can afford, is a daunting & time consuming task. This talk will highlight how you can use Python, PostGIS, Slack, and some regression techniques to find a place to live.
About the Author
As a student of Chemical Engineering at Queen's University, Ian was pursuing a career back home in Calgary, Alberta in the Oil & Gas industry. During one summer, he was thrown into the world of data science when he started trying to make money by using Python to optimize daily fantasy sports lineups. After the oil price crashed, he realized he should probably look for work in another industry. With a new found passion for data science, Ian started his career working for Capital One in Toronto as a data scientist. For close to three years, Ian worked on operational monitoring across the business, credit risk analysis, data infrastructure & risk models. Looking to experience work in another industry, Ian started working as a product data scientist for Shopify where he currently spends his days doing analysis and building data products to help make commerce better for everyone. In his spare time, Ian likes to participate in hackathons, work on side projects and play spikeball.
Talk Details
Date: Sunday Nov. 17
Location: Round Room (PyData Track)
Begin time: 14:45
Duration: 25 minutes