Designing Machine Learning Systems: An Iterative Process for Production-Ready Applications 1st Edition ISBN: 978-1098107963

Designing Machine Learning Systems guides practitioners through building ML systems that work in real-world production environments. This first edition covers the iterative process of designing, developing, and deploying machine learning applications—from problem definition and data engineering to model training, evaluation, and monitoring. Ideal for engineers, data scientists, and technical teams responsible for ML infrastructure and deployment. The book bridges the gap between academic ML theory and practical production challenges, addressing data quality, feature engineering, model selection, and operational considerations. Essential reading for organizations scaling ML initiatives, training teams, and institutions building technical competency in machine learning systems design. ISBN: 978-1098107963