PyDSLA: Dato CEO, Carlos Guestrin, Presents Dato

PyDSLA: Dato CEO, Carlos Guestrin, Presents Dato

*** EVENTBRITE LINK HERE ***

PyDSLA – Dato: A Platform for Practical, Large-Scale Machine Learning

Join PyDSLA for a talk by Carlos Guestrin about Presents Practical, Large-Scale Machine Learning in python.

Summary:

Data Science is perhaps the hottest profession on the market today. Folks with backgrounds ranging from Statistics and Physics to Engineering and Computer Science are eager and excited to transition to this field. However, designing and deploying data analysis and machine learning apps at scale is a significant challenge to overcome: For some folks, machine learning algorithms and methods can be obscure, too mathy, and disconnected from practice. For others, writing and deploying scalable software requires significant effort, which distracts them from focusing on their deep analytic efforts.

In this talk, I will cover a key set of techniques for data engineering, modeling, and deployment, which can help getting started in large-scale machine learning problems.  I will demo these techniques using GraphLab Create, and real-world, large-scale use cases.

 

Bio:

Carlos is the CEO and co-founder of Dato (formerly GraphLab, Inc.) and the Amazon Professor of Machine Learning in Computer Science & Engineering at the University of Washington. A world-recognized leader in the field of Machine Learning, Carlos was named one of the 2008 “Brilliant 10″ by Popular Science Magazine, received the 2009 IJCAI Computers and Thought Award for his contributions to Artificial Intelligence, and a Presidential Early Career Award for Scientists and Engineers (PECASE).

 

Date: May 14, 2015 (Thursday)

Timeline:
– 6:30pm food/bev & networking
– 7:30pm talks starts promptly

You must have a confirmed RSVP and please arrive by 6:55pm the latest. Please RSVP for this meetup here on Eventbrite, as space is limited due to the capacity of the room. Make sure to RSVP now!

Venue: Venice Arts, 1702 Lincoln Blvd, Venice, CA 90291

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