Machine Learning at Scale with H2O
Machine Learning at Scale with H2O helps you to succeed in building and deploying state-of-the-art predictive models with large data volumes in an enterprise setting. The book enables you to understand the perspectives of varied stakeholders while navigating the journey from model development to business value.
Offered by
Difficulty Level
Intermediate
Completion Time
13h12m
Language
English
About Book
Who Is This Book For?
This book is for data scientists and machine learning engineers who want to gain hands-on machine learning experience by building and deploying state-of-the-art models with advanced techniques using H2O technology. An understanding of the data science process and experience in Python programming is recommended. This book will also benefit students by helping them understand how machine learning works in real-world enterprise scenarios.
Machine Learning at Scale with H2O
- About Book
- Who Is This Book For?
- Book Content
Book content
chapters • 13h12m total length
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
Related Resources
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