Part 3 H2O AutoML Advanced Implementation and Productization

This part will help you understand H2O AutoML’s advanced features and parameters used to customize certain characteristics of AutoML to suit specialized needs. This will help you get the desired personalized results that generalized machine learning fails to provide. It will also explain the various ways that H2O AutoML can be used with different types of technologies, and you will understand how you can deploy your machine learning models into production, and commercially use them to meet business needs.

This section comprises the following chapters:

• Chapter 8, Exploring Optional Parameters for H2O AutoML
• Chapter 9, Exploring Miscellaneous Features in H2O AutoML
• Chapter 10, Working with Plain Old Java Objects (POJOs)
• Chapter 11, Working with Model Object Optimized (MOJO)
• Chapter 12, Working with H2O AutoML and Apache Spark
• Chapter 13, Using H2O AutoML with Other Technologies

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