Bộ sách luyện thi ETS 2023 LC&RC
199,000₫
299,000₫
Sách gia công, Bìa mềm
Thể loại:Computers - Computer Science
Năm:2020
In lần thứ:1
Ngôn ngữ:english
Trang:264
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
• Understand the differences between Kubeflow on different cluster types
• Train models using Kubeflow with popular tools including Scikit-learn, TensorFlow, and Apache Spark
• Keep your model up to date with Kubeflow Pipelines
• Understand how to capture model training metadata
• Explore how to extend Kubeflow with additional open source tools
• Use hyperparameter tuning for training
• Learn how to serve your model in production
