The article, Machine learning for Java developers: Algorithms for machine learning, introduced setting up a machine learning algorithm and developing a prediction function in Java. Readers learned the inner workings of a machine learning algorithm and walked through the process of developing and training a model. This article picks up where that one left off. You’ll get a quick introduction to Weka, a machine learning framework for Java. Then, you’ll see how to set up a machine learning data pipeline, with a step-by-step process for taking your machine learning model from development into production. We’ll also briefly discuss how to use Docker containers and REST to deploy a trained ML model in a Java-based production environment.
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