From Model to Market: MLOps Engineering: Versioning, Monitoring, and Deploying AI Models in Production

By RICHARD BOOZMAN

Building a model is only the beginning.

The real challenge is turning that model into a reliable product that runs in production, scales with users, and continues to perform over time.

"From Model to Market" is a practical, engineering focused guide to MLOps. It shows you how to take AI models from experimentation to deployment using Python and modern production workflows.

This book focuses on the systems, processes, and tools required to manage machine learning at scale.

Why MLOps is critical for real world AI

Without proper MLOps practices, even the best models fail in production.

Common challenges include:

lack of version control for models and datainconsistent training and deployment pipelinesperformance degradation over timedifficulty monitoring model behaviorunreliable deployment processes

This book teaches you how to solve these problems with structured approaches.

What you will learnfundamentals of MLOps and production ML systemsmodel versioning and data managementbuilding reproducible training pipelinesdeployment strategies for machine learning modelsmonitoring model performance and driftlogging, observability, and alertingCI and CD for machine learning workflowsscaling inference systemsautomation of model lifecycle managementmaintaining and updating models in production
From experiment to production system

Throughout the book, you will learn how to:

structure machine learning projects for scalabilitytrack experiments and model versionsdeploy models as reliable servicesmonitor and improve models after deploymenthandle model drift and data changesbuild automated pipelines for continuous improvement

Each chapter focuses on real engineering practices used in production.

Practical applicationsdeploying ML models in SaaS productsbuilding recommendation systemsreal time inference servicesAI driven business applicationsenterprise machine learning platforms

These examples reflect real world AI deployment scenarios.

Who this book is formachine learning engineersdata scientistsbackend engineers working with AIDevOps professionals entering MLOpsteams deploying AI systems

If you want to move beyond experimentation and build production ready AI systems, this book provides the roadmap.

Version with control.
Deploy with confidence.
Operate AI systems at scale.

• Format: Paperback
• Language: English
• ISBN: B0GY948S1S
• ISBN13: 9798257910531
• Release Date: April 2026
• Publisher: Independently Published
• Length: 284 Pages
• Weight: 0.84 lbs.
• Dimensions: 0.6" x 6.0" x 9.0"