Subject archive for "model-management," page 4

Data Science

Announcing Trial and Domino 3.5: Control Center for Data Science Leaders

Even the most sophisticated data science organizations struggle to keep track of their data science projects. Data science leaders want to know, at any given moment, not just how many data science projects are in flight but what the latest updates and roadblocks are when it comes to model development and what projects need their immediate attention.

By Domino8 min read

Data Science

Product Management for AI

Pete Skomoroch presented “Product Management for AI” at Rev. This post provides a distilled summary, video, and full transcript.

By Ann Spencer36 min read

Data Science

Themes and Conferences per Pacoid, Episode 10

Co-chair Paco Nathan provides highlights of Rev 2, a data science leaders summit.

By Paco Nathan26 min read

Data Science

Machine Learning Product Management: Lessons Learned

This Domino Data Science Field Note covers Pete Skomoroch’s recent Strata London talk. It focuses on his ML product management insights and lessons learned. If you are interested in hearing more practical insights on ML or AI product management, then consider attending Pete’s upcoming session at Rev.

By Ann Spencer8 min read

Data Science

Announcing Domino 3.4: Furthering Collaboration with Activity Feed

Our last release, Domino 3.3 saw the addition of two major capabilities: Datasets and Experiment Manager. “Datasets”, a high-performance, revisioned data store offers data scientists the flexibility they need to make use of large data resources when developing models. And “Experiment Manager” acts as a data scientist’s “modern lab notebook” for tracking, organizing, and finding everything tested over the course of their research.

By Domino2 min read

Data Science

Themes and Conferences per Pacoid, Episode 9

Paco Nathan's latest article features several emerging threads adjacent to model interpretability.

By Paco Nathan29 min read

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