Learning Ray - Flexible Distributed Python for Machine Learning

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

About the author

Max Pumperla is a data science professor and software engineer located in Hamburg, Germany. He's an active open source contributor, maintainer of several Python packages, and author of machine learning books. He currently works as software engineer at Anyscale. As head of product research at Pathmind Inc. he was developing reinforcement learning solutions for industrial applications at scale using Ray RLlib, Serve and Tune.

Product details

• Authors: Richard Liaw, Edward Oakes, Max Pumperia, Max Pumperla
• Publisher: O'Reilly
• Languages: English
• Product format: Paperback / Softback
• Released: 29.03.2023
• EAN: 9781098117221
• ISBN: 978-1-09-811722-1
• Dimensions: 178 mm x 233 mm x 15 mm
• Weight: 440 g
• Subjects: Natural sciences, medicine, IT, technology > IT, data processing > Programming languages; Data Mining, Programming & scripting languages: general, COMPUTERS / Data Science / Data Visualization, Programming and scripting languages: general, COMPUTERS / Data Science / Data Analytics, COMPUTERS / Database Administration & Management, Data capture and analysis, Data Capture & Analysis, COMPUTERS / Languages / General