MLOps with Ray

Best Practices and Strategies for Adopting Machine Learning Operations
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Paru le : 2024-06-17

Understand how to use MLOps as an engineering discipline to help with the challenges of bringing machine learning models to production quickly and consistently. This book will help companies worldwide to adopt and incorporate machine learning into their processes and products to improve their compet...
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Éditeur

Collection
n.c

Parution
2024-06-17

Pages
338 pages

EAN papier
9798868803758

Auteur(s) du livre


Hien Luu is a passionate AI/ML engineering leader who has been leading the Machine Learning platform at DoorDash since 2020. Hien focuses on developing robust and scalable AI/ML infrastructure for real-world applications. He is the author of  the book Beginning Apache Spark 3 and a speaker at conferences such as MLOps World, QCon (SF, NY, London), GHC 2022, Data+AI Summit, and more. Max Pumperla is a data science professor and software engineer located in Hamburg, Germany. He is an active open source contributor, maintainer of several Python packages, and author of machine learning books. He currently works as a 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. Max has been a core developer of DL4J at Skymind, and helped grow and extend the Keras ecosystem. Zhe Zhang has been leading the Ray Engineering team at Anyscale since 2020. Before that, he was at LinkedIn, managing the Big Data/AI Compute team (providing Hadoop/Spark/TensorFlow as services). Zhe has been working on Open Source for about a decade. Zhe is a committer and PMC member of Apache Hadoop; and the lead author of the HDFS Erasure Coding feature, which is a critical part of Apache Hadoop 3.0. In 2020 Zhe was elected as a Member of the Apache Software Foundation.  

Caractéristiques détaillées - droits

EAN PDF
9798868803765
Prix
64,08 €
Nombre pages copiables
3
Nombre pages imprimables
33
Taille du fichier
8940 Ko
EAN EPUB
9798868803765
Prix
64,08 €
Nombre pages copiables
3
Nombre pages imprimables
33
Taille du fichier
5939 Ko

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