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Machine Learning at Scale with H2O : a Practical Guide to Building and Deploying Machine Learning Models on Enterprise Systems /
Build predictive models using large data volumes and deploy them to production using cutting-edge techniques Key Features Build highly accurate state-of-the-art machine learning models against large-scale data Deploy models for batch, real-time, and streaming data in a wide variety of target product...
| Clasificación: | Libro Electrónico |
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| Autor principal: | |
| Otros Autores: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Birmingham :
Packt Publishing, Limited,
2022.
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| Temas: | |
| Acceso en línea: | Texto completo (Requiere registro previo con correo institucional) |
Tabla de Contenidos:
- Table of Contents Opportunities and Challenges Platform Components and Key Concepts Fundamental Workflow - Data to Deployable Model H2O Model Building at Scale – Capability Articulation Advanced Model Building – Part I Advanced Model Building – Part II Understanding ML Models Putting It All Together Production Scoring and the H2O MOJO H2O Model Deployment Patterns The Administrator and Operations Views The Enterprise Architect and Security Views Introducing the H2O AI Cloud H2O at Scale in a Larger Platform Context Appendix – Alternative Methods to Launch H2O Clusters.