PyData Meetup – February 2018

Tuesday, February 13th, 6:30 PM to 8:30 PM
Microsoft Singapore Auditorium
One Marina Boulevard, Level 21, Conf Room 21MPR-02 Singapore 018989

Agenda

• 6:45pm – 7:00pm Networking
• 7:00pm – 8:15pm Presentation: Cliff Chew
Title: Predicting home wins of NBA games

Synopsis

Like many self-studying data science enthusiast, this side project of mine started with me wanting to apply my data science skills to some real-world data. The topic that I chose on was on a game that I was most passionate about: basketball. Using publicly available NBA (National Basketball Association) match data, I first trained my model to predict the odds of home team wins for an NBA game. Then, with my trained model, I set up a workflow that updates the games data, and makes a daily prediction on existing games.
In this sharing, I will discuss in greater detail my project motivations, considerations, the implementations itself, the challenges I faced, and my current iteration stage.

Bio

Cliff is currently working with digital marketing data at Carousell. When not at work, he tries to read as widely as possible, including things related to programming and data science. Updates