Author archive for Domino, page 6

Domino

Domino powers model-driven businesses with its leading Enterprise AI platform that accelerates the development and deployment of data science work while increasing collaboration and governance. More than 20 percent of the Fortune 100 count on Domino to help scale data science, turning it into a competitive advantage. Founded in 2013, Domino is backed by Sequoia Capital and other leading investors.

Data Science

Managing Data Science as a Capability

Nick Elprin, CEO at Domino, presented a 3-hour training workshop, “Managing Data Science in the Enterprise”, that provided practical insights and interactive breakouts. The learnings, anecdotes, and best practices shared in the workshop were based upon years of candid discussions with customers about managing and accelerating data science work. The workshop also featured reusable templates that included a pre-flight data science project checklist as well as a planning template for hiring and onboarding data scientists. We are sharing the breakout materials based on attendee feedback. If you missed Strata and are interested in joining similar discussions, then consider attending Rev.

By Domino5 min read

Data Science

Docker, but for Data

Aneesh Karve, Co-founder and CTO of Quilt, visited the Domino MeetUp to discuss the evolution of data infrastructure. This blog post provides a session summary, video, and transcript of the presentation. Karve is also the author of "Reproducible Machine Learning with Jupyter and Quilt".

By Domino39 min read

Data Science

0.05 is an Arbitrary Cut Off: "Turning Fails into Wins”

Grace Tang, Data Scientist at Uber, presented insights, common pitfalls, and “best practices to ensure all experiments are useful” in her Strata Singapore session, “Turning Fails into Wins”. Tang holds a Ph.D. in Neuroscience from Stanford University.

By Domino5 min read

Data Science

Racial Bias in Policing: An Analysis of Illinois Traffic Stop Data

Mollie Pettit, Data Scientist and D3.js Data Visualization Instructor with Metis, walks data scientists through analysis of Illinois police traffic stop data, presenting a story narrative of Chicago in 2016. Pettit also discusses how, and shows why, data scientists need to be thoughtful and aware of assumptions when analyzing data and presenting a story narrative.

By Domino14 min read

Data Science

Data Quality Analytics

Scott Murdoch, PhD, Director of Data Science at HealthJoy, presents how data scientists can use distribution and modeling techniques to understand the pitfalls in their data and avoid making decisions based on dirty data.

By Domino17 min read

Data Science

Summertime Analytics: Predicting E. Coli and West Nile Virus

Gene Leynes (Senior Data Scientist) and Nick Lucius (Advanced Analytics) from the City of Chicago discussed two predictive analytics projects that forecasted potential risk involved with E. coli in Lake Michigan and West Nile Virus from mosquitos.

By Domino31 min read

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