Subject archive for "models-featured," page 2

Derrick Higgins of American Family Insurance presented a talk, “Classify all the Things (with multiple labels): The most common type of modeling task no one talks about” at Rev. Higgins covers multilabel classification, a few methods used for multiclass prediction, and existing toolkits. This blog post provides highlights, the video, and a transcript of the talk.

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.

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.

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.

Max Shron, the head of data science at Warby Parker, delivered a presentation on stakeholder-driven data science at a Data Science Popup. This blog post provides a session summary, a video of the entire session, and a video transcript of the presentation. If you are interested in attending a future Data Science Popup, the next event is November 14th in Chicago.