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about the technology

Machine learning system design is complex. The successful ML engineer needs to navigate a multistep process that demands skills from many different fields and roles. This one-of-kind-guide starts by showing you the big picture and then guides you step by step through a framework for creating successful systems. You’ll learn to excel at delivering for global objectives, diving locally into tools, and combining your knowledge into an integrated vision.

about the book

In Machine Learning System Design: With end-to-end examples you’ll find a step-by-step framework for creating, implementing, releasing, and maintaining your ML system. Every part of the life cycle is covered, from information gathering to keeping your system well-serviced. Each stage includes its own handy checklist of requirements and is fully illustrated with real-world examples, including interesting anecdotes from the author’s own careers.

You’ll follow two example companies each building a new ML system, exploring how their needs are expressed in design documents and learning best practices by writing your own. Along the way, you’ll learn how to ace ML system design interviews, even at highly competitive FAANG-like companies, and improve existing ML systems by identifying bottlenecks and optimizing system performance.

about the reader

For readers who know the basics of both software engineering and machine learning. Examples in Python.

about the authors

Arseny Kravchenko is a seasoned ML engineer with a proven track record of building and optimizing reliable ML systems for startups, including real-time video processing, manufacturing optimization, and financial transactions analysis.

Valerii Babushkin is an accomplished data science leader with extensive experience in the tech industry. He currently serves as the VP of Data Science at Blockchain.com, where he is responsible for leading the company's data-driven initiatives. Prior to joining Blockchain.com, Valerii held key roles at leading tech companies, such as Facebook, Alibaba, and X5 Retail Group.