Author archive for Domino, page 5

Wes McKinney, Director of Ursa Labs and creator of pandas project, presented the keynote, "Advancing Data Science Through Open Source" at Rev. McKinney's keynote covered open source's symbiotic relationship with data science and the importance of community-led open source. This blog post includes distilled highlights, the full video, and transcript of the keynote.

At Rev, Nick Elprin, Domino's CEO, continued to provide insights on managing data science based upon years of candid discussions with customers. He also delved into how data science leaders can utilize model management and help their companies become successful model-driven organizations. This blog post provides a distilled summary of the whitepaper, "Introducing Model Management". The whitepaper is a companion to his talk and is also available for download.

Dr. Connie Brett is the owner of Aggregate Genius. Dr. Connie Brett provides custom visualization tool development and support for the Translational Bioinformatics team at Bristol-Myers Squibb and is also the maintainer of the CRAN package for canvasXpress. The team develops and supports tools including canvasXpress to help break down obstacles to scientific research and development.

This Domino Data Science Field Note provides some highlights of Alice Zheng’s report, "Evaluating Machine Learning Models", including evaluation metrics for supervised learning models and offline evaluation mechanisms. The full in-depth report also includes coverage on offline vs online evaluation mechanisms, hyperparameter tuning and potential A/B testing pitfalls is available for download. A distilled slide deck that serves as a complement to the report is also available.

Alex Leeds, presented “Building Up Local Models of Customers” at a Domino Data Science Popup. Leeds discussed how the Squarespace data science team built models to address a key business challenge as well as utilized a complex organizational structure to accelerate data science work. This Domino Data Science Field Note provides highlights and video clips from his talk. The full video recording is also available for viewing. Also, if you would like additional information on building and managing models within an overall data science practice, then consider Domino’s model-management paper or practical guide for managing data science at scale.

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 and local affiliates. Members of Domino were in the live audience for the City Arts talk. This Domino Data Science Field Note provides insights excerpted from Crawford’s City Arts talk and from her NIPS keynote for additional breadth, depth and context for our data science blog readers. This blog post covers Crawford’s research that includes bias as a socio-technical challenge, implications when systems are trained on and ingest biased data, model interpretability, and recommendations for addressing bias.