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.

Java-based machine learning with Weka As you’ve seen, developing and testing a target function requires well-tuned configuration parameters, such as the proper learning rate or iteration count.

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 Deep Java Library: Develop and deploy machine and deep learning models, drawing on MXNet, PyTorch and TensorFlow frameworks. These and other capabilities make Java accessible to developer ...

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 financing from Tencent, SV Angel, GreatPoint Ventures ...

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 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.