Subject archive for "model-management," page 9

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.

This Domino Data Science Field Note provides highlights and video clips from Addhyan Pandey’s Domino Data Pop-Up talk, “Leveraging Data Science in the Automotive Industry.” Addhyan Pandey is the Principal Data Scientist at Cars.com. Highlights covered in this blog post include Pandey using word2vec to identify duplicate vehicles on the platform, how his data science team refers to predictive models as “data products”, and the company’s overall approach to data science. While this post covers highlights and video excerpts, the full video of his talk is available. If this type of content interests you, visit the Domino Data Science Pop-Up Playlist or consider attending Rev.

This Domino Data Science Field Note blog post provides highlights of Hadley Wickham’s ACM Chicago talk, “You Can’t Do Data Science in a GUI”. In his talk, Wickham advocates that, unlike a GUI, using code provides reproducibility, data provenance, and the ability to track changes so that data scientists have the ability to see how the data analysis has evolved. As the creator of ggplot2, it is not a surprise that Wickham also advocates the use of visualizations and models together to help data scientists find the real signals within their data. This blog post also provides clips from the original video and follows the Creative Commons license affiliated with the original video recording.

Speaker Bio: Dr. Vivienne Ming was named one of 10 Women to Watch in Tech by Inc. Magazine, she is a theoretical neuroscientist,entrepreneur, and author. She co-founded Socos Labs, her fifth company, an independent think tank exploring the future of human potential. Dr. Ming launched Socos Labs to combine her varied work with that of other creative experts and expand their impact on global policy issues, both inside companies and throughout our communities. Previously, Vivienne was a visiting scholar at UC Berkeley's Redwood Center for Theoretical Neuroscience, pursuing her research in cognitive neuroprosthetics. In her free time, Vivienne has invented AI systems to help treat her diabetic son, predict manic episodes in bipolar sufferers weeks in advance, and reunited orphan refugees with extended family members. She sits on boards of numerous companies and nonprofits including StartOut, The Palm Center, Cornerstone Capital, Platypus Institute, Shiftgig, Zoic Capital, and SmartStones. Dr. Ming also speaks frequently on her AI-driven research into inclusion and gender in business. For relaxation, she is a wife and mother of two.