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Kubeflow for Machine Learning - From Lab to Production (Paperback)
Loot Price: R850
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Kubeflow for Machine Learning - From Lab to Production (Paperback)
Expected to ship within 12 - 17 working days
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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. Using examples throughout the book, authors Holden
Karau, Trevor Grant, Ilan Filonenko, Richard Liu, and Boris
Lublinsky explain how to use Kubeflow to train and serve your
machine learning models on top of Kubernetes in the cloud or in a
development environment on-premises. Understand Kubeflow's design,
core components, and the problems it solves Learn how to set up
Kubeflow on a cloud provider or on an in-house cluster Train models
using Kubeflow with popular tools including scikit-learn,
TensorFlow, and Apache Spark Learn how to add custom stages such as
serving and prediction Keep your model up-to-date with Kubeflow
Pipelines Understand how to validate machine learning pipelines
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