with end-to-end examples Babushkin, Valerii creator author. Kravchenko, Arseny author. text nyu Shelter Island, NY Manning ©2025 2025 2025 monographic eng

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xxi, 351 pages : illustrations ; 24 cm "Designing and delivering a machine learning system is an intricate multistep process that requires many skills and roles. Whether you're an engineer adding machine learning to an existing application or designing a ML system from the ground up, you need to navigate massive datasets and streams, lock down testing and deployment requirements, and master the unique complexities of putting ML models into production. That's where this book comes in. Machine Learning System Design shows you how to design and deploy a machine learning project from start to finish. You'll follow a step-by-step framework for designing, implementing, releasing, and maintaining ML systems. As you go, requirement checklists and real-world examples help you prepare to deliver and optimize your own ML systems. You'll especially love the campfire stories and personal tips, and ML system design interview tips"-- Part 1. Preparations. Essentials of machine learning system design -- Is there a problem? -- Preliminary research -- Design document -- Part 2. Early stage. Loss functions and metrics -- Gathering datasets -- Validation schemas -- Baseline solution -- Part 3. Intermediate steps. Error analysis -- Training pipelines -- Features and feature engineering -- Measuring and reporting results -- Part 4. Integration and growth. Integration -- Monitoring and reliability -- Serving and inference optimization -- Ownership and maintenance. Valerii Babushkin, Arseny Kravchenko. Includes index. CSE Machine learning Design Machine learning System design Apprentissage automatique Computer science Q325.5 .B235 2025 006.31 Babushkin, Valerii. Shelter Island, NY : Manning Publications, [2025] [First edition]. (OCoLC)1498526194 9781633438750 1633438759 2025388480 NjBwBT 250909 20250909125424.0 44746 eng