Key Features
- Build reproducible ML pipelines with Azure ML CLI and GitHub Actions
- Automate ML workflows end to end, including deployment and monitoring
- Apply LLMOps principles to deploy and manage generative AI responsibly across clouds
- Purchase of the print or Kindle book includes a free PDF eBook
Who this book is for
This book is for DevOps and Cloud engineers and SREs interested in or responsible for managing the lifecycle of machine learning models. Professionals who are already familiar with their ML workloads and want to improve their practices, or those who are new to MLOps and want to learn how to effectively manage machine learning models in this environment, will find this book beneficial. The book is also useful for technical decision-makers and project managers looking to understand the process and benefits of MLOps.