| Description |
1 online resource (280 pages) |
| Summary |
MLOps Engineering at Scale teaches you how to implement efficient machine learning systems using pre-built services from AWS and other cloud vendors. This easy-to-follow book guides you step-by-step as you set up your serverless ML infrastructure, even if you've never used a cloud platform before. You'll also explore tools like PyTorch Lightning, Optuna, and MLFlow that make it easy to build pipelines and scale your deep learning models in production |
| Bibliography |
Includes bibliographical references and index |
| Notes |
Print version record |
| Subject |
Machine learning -- Computer programs
|
| Form |
Electronic book
|
| ISBN |
9781617297762 |
|
1617297763 |
|
9781638356509 |
|
1638356505 |
|
