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On Collaboration Between Data Science, Product, and Engineering Teams

Eugene Mandel, Head of Product at Superconductive Health, recently dropped by Domino HQ to candidly discuss cross-team collaboration within data...

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Reflections on the Data Science Platform Market

Reflections Before we get too far into 2019, I wanted to take a brief moment to reflect on some of the changes we’ve seen in the market. In 2018 we...

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Data Science vs Engineering: Tension Points

This blog post provides highlights and a full written transcript from the panel, “Data Science Versus Engineering: Does It Really Have To Be This Way?

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Collaboration Between Data Science and Data Engineering: True or False?

This blog post includes candid insights about addressing tension points that arise when people collaborate on developing and deploying models....

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Justified Algorithmic Forgiveness?

Last week, Paco Nathan referenced Julia Angwin’s recent Strata keynote that covered algorithmic bias. This Domino Data Science Field Note dives a bit...

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On the Importance of Community-Led Open Source

Wes McKinney, Director of Ursa Labs and creator of pandas project, presented the keynote, "Advancing Data Science Through Open Source" at Rev....

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Model Management and the Era of the Model-Driven Business

Over the past few years, we’ve seen a new community of data science leaders emerge. Regardless of their industry, we have heard three themes emerge...

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On Ingesting Kate Crawford’s “The Trouble with Bias”

Kate Crawford discussed bias at a recent SF-based City Arts and Lectures talk and a recording of the discussion will be broadcast, May 6th, on KQED...

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Data Scientist? Programmer? Are They Mutually Exclusive?

This Domino Data Science Field Note blog post provides highlights of Hadley Wickham’s ACM Chicago talk, “You Can’t Do Data Science in a GUI”. In his...

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The Machine Learning Reproducibility Crisis

Pete Warden is the Technical Lead on the TensorFlow Mobile Embedded Team at Google doing Deep Learning. He is formerly the CTO of Jetpac, which was...

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Data Science Use Cases

In this post, Don Miner covers how to identify, evaluate, prioritize, and pick which data science problems to work on next. Don is a cofounder of ...

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