In today’s fast-evolving technological landscape, the integration of machine learning models into enterprise environments demands a robust framework that bridges development and operations seamlessly. This book presents a production-first approach to MLOps, emphasizing the practicalities of deploying, monitoring, and maintaining machine learning systems at scale within complex organizational settings. It offers readers a comprehensive guide to overcoming typical challenges associated with operationalizing ML, ensuring models deliver consistent business value.

• MLOps as a Discipline: The book posits MLOps not merely as a set of tools, but as an interdisciplinary practice combining software engineering, DevOps, and...
  Full summary available for members

  Our members get access to comprehensive book summaries, key insights, and practical applications.

  Log in or Create a free account