Keys / Whiting Machine Learning at Scale with H2O

A practical guide to building and deploying machine learning models on enterprise systems
1. Auflage 2022
ISBN: 978-1-80056-929-4
Verlag: De Gruyter
Format: EPUB
Kopierschutz: 0 - No protection

E-Book, Englisch, 396 Seiten

No detailed description available for "Machine Learning at Scale with H2O".

Autoren/Hrsg.

Keys, Gregory

Whiting, David

Fachgebiete

• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz
• Mathematik | Informatik EDV | Informatik Business Application Unternehmenssoftware
• Mathematik | Informatik EDV | Informatik Daten / Datenbanken Automatische Datenerfassung, Datenanalyse

Inhaltsverzeichnis

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

Über Autor(innen)

Keys Gregory:

Gregory Keys is a Senior Solution Architect at H2O and has over 20 years of experience designing and implementing software and data systems. He innovated a model deployment and governance framework that was incorporated into Cloudera machine learning product line.Whiting David:

David Whiting is a Data Science Director and Head of Training at H2O.ai. He has over 18 years of experience in business, consulting, and academia. He is adept at developing and maintaining long-term collaborations with experts in multiple fields. He has both led and participated in multi-disciplinary teams and he enjoys mentoring developing analysts and has a substantial experience in doing so.