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    Credit Card Fraud Detection using XGBoost, SMOTE, and threshold moving

    In this article, we'll discuss the challenge organizations face around fraud detection, how machine learning can be used to identify and spot anomalies that the human eye...

    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...

    Model Deployment Powered by Kubernetes

    In this article we explain how we’re using Kubernetes to enable data scientists to deploy predictive models as production-grade APIs. Background ...

    Benchmarking Predictive Models

    It's been said that debugging is harder than programming. If we, as data scientists, are developing models ("programming") at the limits of our...

    Reflections on "buy vs build"

    “Buy vs build”, “not-invented-here syndrome” and even “invented-here-syndrome” have been written about extensively. I want to share a few reflections...