Practical MLOps: Operationalizing Machine Learning Models
Practical MLOps: Operationalizing Machine Learning Models introduces the practices and perspectives involved in moving machine learning models from development into operational environments. Written by Noah Gift and Alfredo Deza, it offers a practical foundation for understanding MLOps and its role in modern software engineering.
About This Book
Practical MLOps: Operationalizing Machine Learning Models focuses on the practical challenges of putting machine learning models into operation.
The book explores MLOps as the discipline connecting machine learning development with the systems, processes, and practices needed for operational use.
It is intended for readers seeking a grounded introduction to managing machine learning models beyond the initial development stage.
With an emphasis on practical application, the book presents MLOps in the context of modern technology and software engineering.
Reviews
No reviews yet. Be the first to review this book!