Learn how to build and deploy a machine-learning data model in a Java-based production environment using Weka, Docker, and REST.

Amazon's Deep Java Library (DJL) is one of several implementations of the new JSR 381 standard for building machine learning applications in Java.

One of these implementations is based on Deep Java Library (DJL), an open source library developed by Amazon to build machine learning in Java.

You can get a good feel for the coverage by counting the samples: There are 54 Java and 60 Scala machine learning examples, 52 Python machine learning examples, and only five R examples.

The key difference between a false positive and a false negative is that a false positive incorrectly asserts that something will happen, while a false negative incorrectly asserts that something will ...

Skymind, a company developing an open-source deep-learning library for Java, along with tools for implementation, today closed $3 million in ...

A big new developer survey shows that Python has finally passed Java in the programming language popularity wars, propelled by its propensity for use in machine learning and data science projects.