Get the big picture and the important details with this end-to-end guide for designing highly effective, reliable machine learning systems. In Machine Learning System Design: With end-to-end examples you will learn: The big picture of machine learning system design Analyzing a problem space to identify the optimal ML solution Ace ML system design interviews Selecting appropriate metrics and evaluation criteria Prioritizing tasks at different stages of ML system design Solving dataset-related problems through data gathering, error analysis, and feature engineering Recognizing common pitfalls in ML system development Designing ML systems to be lean, maintainable, and extensible over time Machine Learning System Design: With end-to-end examples is a practical guide for planning and designing successful ML applications. It lays out a clear, repeatable framework for building, maintaining, and improving systems at any scale. Authors Arseny Kravchenko and Valeri Babushkin have filled this unique handbook with campfire stories and personal tips from their own extensive careers. You'll learn directly from their experience as you consider every facet of a machine learning system, from requirements gathering and data sourcing to deployment and management of the finished system.
Read More
Specifications
Book Details
Imprint
Manning Publications
Publication Year
2025 2025
Edition Type
1
Table of Contents
Table of Contents
Part 1
1 Essentials of machine learning system design
2 Is there a problem?
3 Preliminary research
4 Design document
Part 2
5 Loss functions and metrics
6 Gathering datasets
7 Validation schemas
8 Baseline solution
Part 3
9 Error analysis
10 Training pipelines
11 Features and feature engineering
12 Measuring and reporting results
Part 4
13 Integration
14 Monitoring and reliability
15 Serving and inference optimization
16 Ownership and maintenance
Contributors
Author Info
About the Author
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.
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.
Dimensions
Width
20 mm
Height
235 mm
Length
187 mm
Depth
2
Weight
685 gr
Be the first to ask about this product
Safe and Secure Payments.Easy returns.100% Authentic products.