Practical Automated Machine Learning Using H2O.ai

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Working with Plain Old Java Objects (POJOs)

Companies often use a mix of strategies that can deliver services up to the expected standards. In the case of services that use Machine Learning (ML), they need to consider how they can quickly and easily build, extract, and deploy their models in production without affecting their ongoing service.

Hence, the portability of trained models is very important. How do you take a model object created by your training pipeline built with a certain technology and use that in your prediction pipeline, which might be built using a different technology? Ideally, the model object should be an object that is self-contained and easily distributable.

In the world of software engineering, the Java programming ...