Erhältlich:
Nicht auf Lager
Buch (Softcover): Fachbuch
Machine Learning Production Systems
Engineering Machine Learning Models and Pipelines
Produkt bewerten
Verlag:
O'Reilly Unsere-Artikel-Nr.: QEDVYLW
EAN: 9781098156015
Erhältlich:
Nicht auf Lager
Zustellung: Di, 21.07.2026
Versand: Kostenlos
-22.2 %
CHF 106.–
CHF 82.50
Beschreibung
Using machine learning for products, services, and critical business processes is quite different from using ML in an academic or research setting-especially for recent ML graduates and those moving from research to a commercial environment. Whether you currently work to create products and services that use ML, or would like to in the future, this practical book gives you a broad view of the entire field. Authors Robert Crowe, Hannes Hapke, Emily Caveness, and Di Zhu help you identify topics that you can dive into deeper, along with reference materials and tutorials that teach you the details. You'll learn the state of the art of machine learning engineering, including a wide range of topics such as modeling, deployment, and MLOps. You'll learn the basics and advanced aspects to understand the production ML lifecycle. This book provides four in-depth sections that cover all aspects of machine learning engineering: Data:. collecting, labeling, validating, automation, and data preprocessing; data feature engineering and selection; data journey and storage Modeling:. high performance modeling; model resource management techniques; model analysis and interoperability; neural architecture search Deployment:. model serving patterns and infrastructure for ML models and LLMs; management and delivery; monitoring and logging Productionalizing:. ML pipelines; classifying unstructured texts and images; genAI model pipelines
Spezifikationen
Sprache
- Englisch
Autor
- Crowe Robert
- Hannes Hapke
- Emily Caveness
- Di Zhu
Erscheinungsjahr
- 2024
Format
- Buch (Softcover)