Reliable Machine Learning: Applying SRE Principles to ML in Production

This book provides practical guidance for running machine learning (ML) reliably, effectively, and accountably within organizations of all sizes. It covers topics such as model monitoring, team management, and integrating ML into production systems, with an emphasis on applying an SRE mindset to ML. By following the steps outlined in this book, data scientists, SREs, and business owners can build efficient ML systems that help increase revenue, optimize decision-making, solve problems, and understand and influence customer behavior.

Format: Paperback / softback
Length: 350 pages
Publication date: 30 September 2022
Publisher: O'Reilly Media

This comprehensive guide is designed for data scientists, software engineers, and business owners who want to implement machine learning (ML) systems reliably, efficiently, and responsibly within their organizations. Whether you're part of a small startup or a global conglomerate, this practical book offers valuable insights and strategies for running ML operations effectively.

By adopting an SRE (Site Reliability Engineering) mindset to ML, the authors, along with engineering professionals and featured guests, demonstrate how to establish an efficient ML system. Whether your goal is to boost revenue, optimize decision-making, address complex problems, or gain a deeper understanding of customer behavior, this guide will empower you to perform day-to-day ML tasks while keeping a broader perspective in mind.

In this comprehensive guide, you will explore:

What ML is: Understanding its core concepts, how it works, and the underlying principles that drive it.

Conceptual frameworks for understanding the intricate loops and processes involved in ML systems.

Effective productionization: Learn how to make ML systems easily monitorable, deployable, and operable, ensuring seamless integration into your production environment.

Challenges associated with ML systems in production environments, and strategies to overcome them.

Effective communication between ML, product, and production teams is crucial for successful ML implementation. By fostering collaboration and understanding, you can ensure that ML initiatives align with business objectives and drive tangible results.

Whether you're a seasoned ML professional or just starting your journey, this guide provides valuable insights and practical techniques to help you run ML systems reliably, efficiently, and accountably. By applying an SRE mindset to ML, you can unlock the full potential of this powerful technology and drive innovation within your organization.

Weight: 716g
Dimension: 177 x 233 x 25 (mm)
ISBN-13: 9781098106225