Edwin Thoen • 5/14/2020

Using {drake} for Machine Learning

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This article details the author's experience adopting the {drake} R package for managing complex machine learning workflows. It compares their approach to a previously published workflow, emphasizing how drake solves issues like dependency management, caching intermediate results, and ensuring reproducibility in projects that span months. The focus is on building a coherent, production-ready model pipeline.

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#Machine Learning #workflow automation #Reproducibility
Using {drake} for Machine Learning

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