Wisdom From Machine Learning at Netflix

At Data By The Bay in May, we saw a great talk by Netflix’s Justin Basilico: Recommendations for Building Machine Learning Software. Justin describes some principles for effectively developing machine learning algorithms and integrating them into software products. We found ourselves nodding violently in agreement, and we wanted to recapitulate a few of his points […]

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Choosing Content for Netflix: How Data Leads the Way

This talk took place at the Domino Data Science Pop-up in Los Angeles, CA on September 14, 2016 In this presentation, Paul Ellwood, VP of Data Engineering & Analytics at Netflix, talks about how the leading data-driven entertainment company uses data science to choose content for over 80 million global subscribers.   The company who […]

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VCs Developing In-House Tech-Expertise-as-a-Service

Ashlee Vance writes in “Netflix Loses Its Cloud Guru to a VC Firm”: “It used to be good enough for venture capitalists just to hand out money. Well, not anymore. Now they’re expected to offer up a suite of services and give their startups access to things like marketing coaches and technical advisors.” Vance mentions […]

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7 Observations from the Big Data Innovation Summit

The Innovation Enterprise events group put together recently the second annual Big Data Innovation Summit in Boston. Here are a few of the highlights of the first day: Banana production in Central America is twice the rate of trash production in New York City This and similar “fun facts” from Wolfram Alpha would have pleased Oscar Wilde […]

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Big Data Analytics and Data Science at Netflix (Video)

Chris Pouliot, the Director of Analytics and Algorithms at Netflix: “…my team does not only personalizations for movies, but we also deal with content demand prediction. Helping our buyer down in Beverly Hills figure out how much do we pay for a piece of content. The personalization recommendations for helping users find good movies and […]

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