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Data By the Bay is the first Data Grid conference matrix with 6 vertical application areas  spanned by multiple horizontal data pipelines, platforms, and algorithms.  We are unifying data science and data engineering, showing what really works to run businesses at scale.
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Thursday, May 19 • 11:40am - 12:20pm
Recommendations for Building Machine Learning Software

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Building a real system that uses machine learning can be a difficult both in terms of the algorithmic and engineering challenges involved. In this talk, I will focus on the engineering side and discuss some of the practical lessons we’ve learned from years of developing the machine learning systems that power Netflix. I will go over what it takes to get machine learning working in a real-life feedback loop with our users and how that imposes different requirements and a different focus than doing machine learning only within a lab environment. This involves lessons around challenges such as where to place algorithmic components, how to handle distribution and parallelism, what kinds of modularity are useful, how to support both production experimentation, and how to test machine learning systems.

Speakers
avatar for Justin Basilico

Justin Basilico

Research/Engineering Manager, Netflix
Justin Basilico is a Research/Engineering Manager for Page Algorithms Engineering at Netflix. He leads an applied research team focused on developing the next generation of algorithms used to generate the Netflix homepage through machine learning, ranking, recommendation, and large-scale software engineering. Prior to Netflix, he worked on machine learning in the Cognitive Systems group at Sandia National Laboratories. He is also the co-creator... Read More →



Thursday May 19, 2016 11:40am - 12:20pm
Ada

Attendees (23)