Skip to content
    Latest

    The Importance of Machine Learning Model Validation and How It Works

    Model valuation is a core component of developing machine learning or artificial intelligence (ML/AI). While it’s separate from training and deployment, it should pervade the...

    Themes and Conferences per Pacoid, Episode 7

    Paco Nathan covers recent research on data infrastructure as well as adoption of machine learning and AI in the enterprise. Introduction Welcome...

    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...

    Item Response Theory in R for Survey Analysis

    In this guest blog post, Derrick Higgins, of American Family Insurance, covers item response theory (IRT) and how data scientists can apply it within...

    Feature Engineering: A Framework and Techniques 

    This Domino Field Note provides highlights and excerpted slides from Amanda Casari’s “Feature Engineering for Machine Learning” talk at QCon Sao...

    The Past/Present/Future + Myths of Data Science

    Sivan Aldor-Noiman, VP of Data Science at Wellio, presented “The Past/Present/Future + Myths of Data Science” at Domino. This blog post provides a...

    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...