Author archive for Domino, page 4

Domino

Domino Data Lab empowers the largest AI-driven enterprises to build and operate AI at scale. Domino’s Enterprise AI Platform unifies the flexibility AI teams want with the visibility and control the enterprise requires. Domino enables a repeatable and agile ML lifecycle for faster, responsible AI impact with lower costs. With Domino, global enterprises can develop better medicines, grow more productive crops, develop more competitive products, and more. Founded in 2013, Domino is backed by Sequoia Capital, Coatue Management, NVIDIA, Snowflake, and other leading investors.

Perspective

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. Domino’s Head of Content sat down with Don Miner and Marshall Presser to discuss the state of collaboration between data science and data engineering. The blog post provides distilled insights, audio clips, excerpted quotes as well as the full audio and written transcript. Additional content on this topic will be forthcoming from additional industry experts.

By Domino32 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

Learn from the Reproducibility Crisis in Science

Key highlights from Clare Gollnick’s talk, “The limits of inference: what data scientists can learn from the reproducibility crisis in science”, are covered in this Domino Data Science Field Note. The full video is available for viewing here.

By Domino5 min read

Data Science

Three Simple Worrying Stats Problems

In this guest post, Sean Owen, writes about three data situations that provide ambiguous results and how causation helps clarifies the interpretation of data. A version of this post previously appeared on Quora. Domino would like to extend special thanks to Sean for updating the Quora post for our blog.

By Domino13 min read

Data Science

The Past/Present/Future + Myths of Data Science

Sivan Aldor-Noiman, VP of Data Science at Wellio (now part of The Kraft Heinz Company), presented “The Past/Present/Future + Myths of Data Science” at Domino. This blog post provides a few highlights from the interactive talk as well as the full video.

By Domino4 min read

Data Science

Classify All the Things (with Multiple Labels)

Derrick Higgins of American Family Insurance presented a talk, “Classify all the Things (with multiple labels): The most common type of modeling task no one talks about” at Rev. Higgins covers multilabel classification, a few methods used for multiclass prediction, and existing toolkits. This blog post provides highlights, the video, and a transcript of the talk.

By Domino42 min read

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