Four short links: 16 September 2015

Data Pipelines, Amazon Culture, Real-time NFL Data, and Deep Learning for Chess

  1. Three Best Practices for Building Successful Data Pipelines (Michael Li) — three key areas that are often overlooked in data pipelines, and those are making your analysis: reproducible, consistent, and productionizable.
  2. Amazon’s Culture Controversy Decoded (Rita J King) — very interesting culture map analysis of the reports of Amazon’s culture, and context for how companies make choices about what to be. (via Mike Loukides)
  3. How Will Real-Time Tracking Change the NFL? (New Yorker) — At the moment, the NFL is being tightfisted with the data. Commentators will have access during games, as will the betting and analytics firm Sportradar. Users of the league’s Xbox One app, which provides an interactive way of browsing video clips, fantasy-football statistics, and other metrics, will be able to explore a feature called Next Gen Replay, which allows them to track each player’s speed and trajectory, combining moving lines on a virtual field with live footage from the real one. But, for now, coaches are shut out; once a player exits the locker room on game day, the dynamic point cloud that is generated by his movement through space is a corporately owned data set, as outlined in the league’s 2011 collective-bargaining agreement. Which should tell you all you need to know about the NFL’s role in promoting sporting excellence.
  4. Giraffe: Using Deep Reinforcement Learning to Play Chess (Matthew Lai) — Giraffe, a chess engine that uses self-play to discover all its domain-specific knowledge, with minimal hand-crafted knowledge given by the programmer. See also the code. (via GitXiv)
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