Subject archive for "data," page 4

Data Science

Reflections on the Data Science Platform Market

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 saw the “data science platform” market rapidly crystallize into three distinct product segments. This post describes our observations about these three segments and offers advice for folks evaluating products in this space.

By Nick Elprin8 min read

Data Science

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?” with Amy Heineike, Paco Nathan, and Pete Warden at Domino HQ. Topics discussed include the current state of collaboration around building and deploying models, tension points that potentially arise, as well as practical advice on how to address these tension points.

By Ann Spencer99 min read

Data Science

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?” with Amy Heineike, Paco Nathan, and Pete Warden at Domino HQ. Topics discussed include the current state of collaboration around building and deploying models, tension points that potentially arise, as well as practical advice on how to address these tension points.

By Ann Spencer99 min read

Data Science

Domino 3.0: New Features and User Experiences to Help the World Run on Models

This blog post introduces new Domino 3.0 features. Akansh Murthy is a Technical Product Manager at Domino and previously worked as a software engineer at Domino and Kareo.

By Akansh Murthy7 min read

Data Science

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 deeper into some of the publicly available research regarding algorithmic accountability and forgiveness, specifically around a proprietary black box model used to predict the risk of recidivism, or whether someone will “relapse into criminal behavior”.

By Domino14 min read

Data Science

Themes and Conferences per Pacoid, Episode 1

Introduction: New Monthly Series!

By Paco Nathan11 min read

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