"data science teams" entries
The O’Reilly Data Show podcast: Eric Colson on algorithms, human computation, and building data science teams.
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In this episode of the O’Reilly Data Show, I spoke with Eric Colson, chief algorithms officer at Stitch Fix, and former VP of data science and engineering at Netflix. We talked about building and deploying mission-critical, human-in-the-loop systems for consumer Internet companies. Knowing that many companies are grappling with incorporating data science, I also asked Colson to share his experiences building, managing, and nurturing, large data science teams at both Netflix and Stitch Fix.
Augmented systems: “Active learning,” “human-in-the-loop,” and “human computation”
We use the term ‘human computation’ at Stitch Fix. We have a team dedicated to human computation. It’s a little bit coarse to say it that way because we do have more than 2,000 stylists, and these are very much human beings that are very passionate about fashion styling. What we can do is, we can abstract their talent into—you can think of it like an API; there’s certain tasks that only a human can do or we’re going to fail if we try this with machines, so we almost have programmatic access to human talent. We are allowed to route certain tasks to them, things that we could never get done with machines. … We have some of our own proprietary software that blends together two resources: machine learning and expert human judgment. The way I talk about it is, we have an algorithm that’s distributed across the resources. It’s a single algorithm, but it does some of the work through machine resources, and other parts of the work get done through humans.
An introduction to the big data landscape.
It's the hot trend in software right now, but what does big data mean, and how can you exploit it? Strata chair Edd Dumbill presents an introduction and orientation to the big data landscape.
DJ Patil on the traits of data scientists and how data science will evolve within companies.
DJ Patil, data scientist in residence at Greylock Partners, discusses the key trait data scientists need and the obstacles data scientists face within organizations.