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MLOps with Ray
- Best Practices and Strategies for Adopting Machine Learning Operations
Engelsk Paperback
MLOps with Ray
- Best Practices and Strategies for Adopting Machine Learning Operations
Engelsk Paperback

478 kr
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Om denne bog
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 competitiveness. The book delves into this engineering discipline's aspects and components and explores best practices and case studies. Adopting MLOps requires a sound strategy, which the book's early chapters cover in detail. The book also discusses the infrastructure and best practices of Feature Engineering, Model Training, Model Serving, and Machine Learning Observability. Ray, the open source project that provides a unified framework and libraries to scale machine learning workload and the Python application, is introduced, and you will see how it fits into the MLOps technical stack. This book is intended for machine learning practitioners, such as machine learning engineers, and data scientists, who wish to help their company by adopting, building maps, and practicing MLOps.  What You'll LearnGain an understanding of the MLOps disciplineKnow the MLOps technical stack and its componentsGet familiar with the MLOps adoption strategyUnderstand feature engineering Who This Book Is ForMachine learning practitioners, data scientists, and software engineers who are focusing on building machine learning systems and infrastructure to bring ML models to production  
Product detaljer
Sprog:
Engelsk
Sider:
338
ISBN-13:
9798868803758
Indbinding:
Paperback
Udgave:
ISBN-10:
8868803755
Kategori:
Udg. Dato:
18 jun 2024
Længde:
0mm
Bredde:
178mm
Højde:
254mm
Forlag:
Springer-Verlag Berlin and Heidelberg GmbH & Co. KG
Oplagsdato:
18 jun 2024
Forfatter(e):
Books from the same author
Kategori sammenhænge