Subject archive for "data," page 5
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
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.
By Domino3 min read
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.
By Domino10 min read
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.
By Domino11 min read
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
The team at Domino is proud to be named a Visionary for the second year in a row in Gartner’s Magic Quadrant for Data Science and Machine Learning Platforms. It is exciting to see that companies and industry analysts are increasingly realizing the value of a data science platform, and we’re honored to be recognized. It was particularly gratifying to hear feedback from our customers synthesized and channeled through Gartner’s report.
By Mac Steele3 min read
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