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Engineering MLOps : rapidly build, test, and manage production-ready machine learning life cycles at scale /
Engineering MLOps will help you get to grips with ML lifecycle management and MLOps implementation for your organization. This book presents comprehensive insights into MLOps coupled with real-world examples that will teach you how to write programs, train robust and scalable ML models, and build ML...
| Clasificación: | Libro Electrónico |
|---|---|
| Autor principal: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Birmingham :
Packt Publishing, Limited,
2021.
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| Temas: | |
| Acceso en línea: | Texto completo (Requiere registro previo con correo institucional) |
Tabla de Contenidos:
- Table of Contents Fundamentals of MLOps Workflow Characterizing your Machine learning problem Code Meets Data Machine Learning Pipelines Model evaluation and packaging Key principles for deploying your ML system Building robust CI and CD pipelines APIs and microservice Management Testing and Securing Your ML Solution Essentials of Production Release Key principles for monitoring your ML system Model Serving and Monitoring Governing the ML system for Continual Learning.