In this article, we demonstrate how Java developers can use the JSR-381 VisRec API to implement image classification or object detection with DJL’s pre-trained models in less than 10 lines of code.

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

In this blog, I outline briefly: - Common Applications of Data Science - Definitions: Machine learning, deep learning, data engineering and data science - Why Java for data science workflows, for ...

Amazon’s DJL is a deep learning toolkit used to develop machine learning (ML) and deep learning (DL) models natively in Java while simplifying the use of deep learning frameworks.

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

In just 5 minutes, dive into the world of 15 powerful programming languages that shape the tech world. JavaScript, one of the ...

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 ...

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.