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    The Role of Containers on MLOps and Model Production

    Container technology has changed the way data science gets done. The original container use case for data science focused on what I call, “environment management”....

    HyperOpt: Bayesian Hyperparameter Optimization

    This article covers how to perform hyperparameter optimization using a sequential model-based optimization (SMBO) technique implemented in the...

    Deep Reinforcement Learning

    This article provides an excerpt "Deep Reinforcement Learning" from the book, Deep Learning Illustrated by Krohn, Beyleveld, and Bassens. The article...

    Seeking Reproducibility within Social Science: Search and Discovery

    Julia Lane, NYU Professor, Economist and cofounder of the Coleridge Initiative, presented “Where’s the Data: A New Approach to Social Science Search...

    Model Interpretability with TCAV (Testing with Concept Activation Vectors)

    This Domino Data Science Field Note provides very distilled insights and excerpts from Been Kim’s recent MLConf 2018 talk and research about Testing...

    Classify all the Things (with Multiple Labels)

    Derrick Higgins of American Family Insurance presented a talk, “Classify all the Things (with multiple labels): The most common type of modeling task...

    Model Evaluation

    This Domino Data Science Field Note provides some highlights of Alice Zheng’s report, "Evaluating Machine Learning Models", including evaluation...

    Data Science Models Build on Each Other

    Alex Leeds, presented “Building Up Local Models of Customers” at a Domino Data Science Popup. Leeds discussed how the Squarespace data science team...

    Stakeholder-Driven Data Science at Warby Parker

    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...