Practical MLOps: Operationalizing Machine Learning Models 1st Edition ISBN: 978-1098103019

Practical MLOps guides teams through the complete lifecycle of deploying and maintaining machine learning models in production environments. This first edition covers essential practices for model versioning, monitoring, and governance—critical for organizations scaling ML initiatives across teams and infrastructure. Ideal for data engineers, ML engineers, and DevOps professionals responsible for operationalizing models, this book bridges the gap between research and production. Topics include containerization, CI/CD pipelines, model serving, performance tracking, and incident response. Whether you're building internal ML systems or supporting enterprise deployments, this resource provides actionable frameworks and real-world patterns for reliable, maintainable ML operations.