Implementing MLOps in the Enterprise

Implementing MLOps in the Enterprise
A Production-First Approach
Published by O’Reilly

Written by Yaron Haviv and Noah Gift

“Implementing MLOps in the Enterprise: A Production-First Approach” is a practical guide, authored by MLOps veterans Yaron Haviv and Noah Gift and published by O’Reilly, which guides leaders of data science, MLOps, ML engineering and data engineering on how to bring data science to life for a variety of real-world AI and GenAI scenarios. Drawing from their extensive experience in the field, the authors share their strategies, methodologies, tools and best practices for designing and building a continuous, automated and scalable ML pipeline that delivers business value. With practical code examples and specific tool recommendations, the book empowers readers to implement the concepts effectively. After reading the book, ML practitioners and leaders will know how to deploy their ML models to production and scale their AI initiatives, while overcoming the challenges many other businesses are facing.

This excerpt contains Chapters 1 and 2. The complete book is available on the O’Reilly Online Learning Platform and through other retailers.

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