Learning Ray Flexible Distributed Python for Machine Learning

Learning Ray: Flexible Distributed Python for Machine Learning 1st Edition
by Max Pumperla , Edward Oakes, Richard Liaw(Author)
Publisher Finelybook 出版社: O'Reilly Media; 1st edition (March 21, 2023)
Language 语言: English
pages 页数: 271 pages
ISBN-10 书号: 1098117220
ISBN-13 书号: 9781098117221

Book Description

Get started with Ray, the open source distributed computing framework that simplifies the process of scaling compute-intensive Python workloads. With this practical book, Python programmers, data engineers, and data scientists will learn how to leverage Ray locally and spin up compute clusters. You'll be able to use Ray to structure and run machine learning programs at scale.

Authors Max Pumperla, Edward Oakes, and Richard Liaw show you how to build machine learning applications with Ray. You'll understand how Ray fits into the current landscape of machine learning tools and discover how Ray continues to integrate ever more tightly with these tools. Distributed computation is hard, but by using Ray you'll find it easy to get started.

Learn how to build your first distributed applications with Ray Core
Conduct hyperparameter optimization with Ray Tune
Use the Ray RLlib library for reinforcement learning
Manage distributed training with the Ray Train library
Use Ray to perform data processing with Ray Datasets
Learn how work with Ray Clusters and serve models with Ray Serve
Build end-to-end machine learning applications with Ray AIR

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