Practical Automated Machine Learning Using H2O.ai.

Table of Contents

1. Understanding H2O AutoML Basics
2. Working with H2O Flow (H2O's Web UI)
3. Understanding Data Processing
4. Understanding H2O AutoML Training and Architecture
5. Understanding AutoML Algorithms
6. Understanding H2O AutoML Leaderboard and Other Performance Metrics
7. Working with Model Explainability
8. Exploring Optional Parameters for H2O AutoML
9. Exploring Miscellaneous Features in H2O AutoML
10. Working with Plain Old Java Objects (POJOs)
11. Working with Model Object, Optimized (MOJO)
12. Working with H2O AutoML and Apache Spark
13. Using H2O AutoML with Other Technologies