Intro to Machine Learning
Details
The deadline to register and pay online is:
12 Noon Th 4/12
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https://en.wikipedia.org/wiki/Machine_learning
Beneath the hype about machine learning are surprisingly simple concepts that anyone can understand. In this talk, the speaker will answer basic questions like:
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What is machine learning?
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What is a predictive model?
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What does it mean to "train" a model on data?
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How do we know if a model actually reflects reality?
and more!
Far from being a dry and academic topic, machine learning turns out to be useful and practical. This talk is intended for a general audience.
Please come with your questions, comments, and scenarios.
Agenda
6:30 pm to 7:00 pm Check In, Food, Networking
7:00 pm to 8:30 pm Presntation, Q & A
8:30 pm to 9:00 pm More Networking
About the Speaker:
David Gerster is Vice President of Data Science at BigML, an organization founded in 2010 "with the mission of making machine learning easy and beautiful for everyone". David's role is to promote the idea that data science is easy by speaking at conferences and teaching workshops. Since joining BigML in July 2013, he has spoken at CERN, Big Data Spain, Papis.io, DataLead (UC Berkeley), DataBeat (VentureBeat), and more than a dozen other events.
Prior to BigML, David held postions at Groupon and Yahoo. At Groupon, he built an elite data science team that trained the first machine-learned models for mobile deal relevance. At Yahoo, he led the project to collect billions of URL clickstreams in Hadoop and use them to improve Yahoo’s main web search algorithm.
David holds an MBA from the University of California at Berkeley and a bachelor’s degree from Harvard University.
http://linkedin.com/in/gerster ( https://www.linkedin.com/in/gerster )
Intro to Machine Learning