Subject archive for "domino-data-science-field-note"
This Domino Data Science Field Note covers a proposed definition of interpretability and distilled overview of the PDR framework. Insights are drawn from Bin Yu, W. James Murdoch, Chandan Singh, Karl Kumber, and Reza Abbasi-Asi's recent paper, "Definitions, methods, and applications in interpretable machine learning".
By Ann Spencer9 min read
This Domino Data Science Field Note covers Pete Skomoroch’s recent Strata London talk. It focuses on his ML product management insights and lessons learned. If you are interested in hearing more practical insights on ML or AI product management, then consider attending Pete’s upcoming session at Rev.
By Ann Spencer8 min read
This Domino Data Science Field Note provides highlights and excerpted slides from Chloe Mawer’s "The Ingredients of a Reproducible Machine Learning Model" talk at a recent WiMLDS meetup. Mawer is a Principal Data Scientist at Lineage Logistics as well as an Adjunct Lecturer at Northwestern University. Special thanks to Mawer for the permission to excerpt the slides in this Domino Data Science Field Note. The full deck is available here.
By Ann Spencer7 min read
This Domino Data Science Field Note provides very distilled insights and excerpts from Been Kim’s recent MLConf 2018 talk and research about Testing with Concept Activation Vectors (TCAV), an interpretability method that allows researchers to understand and quantitatively measure the high-level concepts their neural network models are using for prediction, “even if the concept was not part of the training". If interested in additional insights not provided in this blog post, please refer to the MLConf 2018 video, the ICML 2018 video, and the paper.
By Domino6 min read
Last week, Paco Nathan referenced Julia Angwin’s recent Strata keynote that covered algorithmic bias. This Domino Data Science Field Note dives a bit deeper into some of the publicly available research regarding algorithmic accountability and forgiveness, specifically around a proprietary black box model used to predict the risk of recidivism, or whether someone will “relapse into criminal behavior”.
By Domino14 min read
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