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Kubeflow for Machine Learning
From Lab to Production
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Zum Merkzettel
Gewicht:
470 g
Format:
233x179x21 mm
Beschreibung:
Trevor Grant is a member of the Apache Software Foundation, and is heavily involved in the Apache Mahout, Apache Streams, and Community Development projects. He often tinkers and occasionally documents his (mis)adventures at rawkintrevo.org. In the before time, he was an international speaker on technology, but now he focuses mainly on writing. Trevor wishes to thank IBM for their continued patronage of his artistic endeavors. He lives in Chicago because it's the best city on the planet, with world class food, parks, and culture, and because the skies are never orange.
If you're training a machine learning model but aren't sure how to put it into production, this book will get you there. Kubeflow provides a collection of cloud native tools for different stages of a model's lifecycle, from data exploration, feature preparation, and model training to model serving. This guide helps data scientists build production-grade machine learning implementations with Kubeflow and shows data engineers how to make models scalable and reliable.