Key Features
- This second edition delves deeper into key machine learning topics, CI/CD, and system design
- Explore core MLOps practices, such as model management and performance monitoring
- Build end-to-end examples of deployable ML microservices and pipelines using AWS and open-source tools
Who this book is for
This book is designed for MLOps and ML engineers, data scientists, and software developers who want to build robust solutions that use machine learning to solve real-world problems. If you’re not a developer but want to manage or understand the product lifecycle of these systems, you’ll also find this book useful. It assumes a basic knowledge of machine learning concepts and intermediate programming experience in Python. With its focus on practical skills and real-world examples, this book is an essential resource for anyone looking to advance their machine learning engineering career.