
Engineering MLOps: Rapidly Build, Test, and Manage Production-ready Machine Learning Life Cycles at Scale
by Various (2021)
Like 'Introducing MLOps', this book offers practical guidance on managing the ML lifecycle at scale.

by Mark Treveil, et al.
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by Various (2021)
Like 'Introducing MLOps', this book offers practical guidance on managing the ML lifecycle at scale.

by Andriy Burkov (2022)
Similar to 'Introducing MLOps', it provides field-tested patterns for building production-ready ML systems.

by Mark Treveil, Nicolas Omont, Clément Stenac
This book, like 'Introducing MLOps', focuses on the core principles of operationalizing ML models.

by Chip Huyen (2022)
Echoing 'Introducing MLOps', this book provides a holistic approach to building robust ML systems.

by Various (2021)
Following the spirit of 'Introducing MLOps', this book explores managing the ML production lifecycle with Python.
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