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The Whys and Hows of Managing Machine Learning Artifacts with Lukas Biewald - #373

The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)

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Navigating Machine Learning Artifacts

This chapter explores the exciting transition to video interviews while introducing a new tool aimed at managing machine learning artifacts. The speakers discuss the importance of efficiently tracking datasets, models, and pipelines, along with the challenges of data provenance and reproducibility in machine learning. They emphasize the need for interoperability within the ecosystem and analyze the complexities faced by companies dealing with dynamic data environments.

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