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Machine Learning at Scale with H2O

You're reading from   Machine Learning at Scale with H2O A practical guide to building and deploying machine learning models on enterprise systems

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Product type Paperback
Published in Jul 2022
Publisher Packt
ISBN-13 9781800566019
Length 396 pages
Edition 1st Edition
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Authors (2):
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Gregory Keys Gregory Keys
Author Profile Icon Gregory Keys
Gregory Keys
David Whiting David Whiting
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David Whiting
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Table of Contents (22) Chapters Close

Preface 1. Section 1 – Introduction to the H2O Machine Learning Platform for Data at Scale
2. Chapter 1: Opportunities and Challenges FREE CHAPTER 3. Chapter 2: Platform Components and Key Concepts 4. Chapter 3: Fundamental Workflow – Data to Deployable Model 5. Section 2 – Building State-of-the-Art Models on Large Data Volumes Using H2O
6. Chapter 4: H2O Model Building at Scale – Capability Articulation 7. Chapter 5: Advanced Model Building – Part I 8. Chapter 6: Advanced Model Building – Part II 9. Chapter 7: Understanding ML Models 10. Chapter 8: Putting It All Together 11. Section 3 – Deploying Your Models to Production Environments
12. Chapter 9: Production Scoring and the H2O MOJO 13. Chapter 10: H2O Model Deployment Patterns 14. Section 4 – Enterprise Stakeholder Perspectives
15. Chapter 11: The Administrator and Operations Views 16. Chapter 12: The Enterprise Architect and Security Views 17. Section 5 – Broadening the View – Data to AI Applications with the H2O AI Cloud Platform
18. Chapter 13: Introducing H2O AI Cloud 19. Chapter 14: H2O at Scale in a Larger Platform Context 20. Other Books You May Enjoy Appendix : Alternative Methods to Launch H2O Clusters

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