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.

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.

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

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.

As the tech world charges into 2025, O'Reilly Media's latest report on its learning platform usage offers a deep dive into the shifting sands of software development education. Among the most ...

The AWS AI Practitioner exam consists of 85 questions that must be completed in 120 minutes. The exam costs 75 US dollars and can be taken online or at a testing center. The passing score is 700 out ...

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 ...