DJL

Deep Java Library (DJL)

Deep Java Library (DJL) is an open-source framework that helps developers build, deploy and maintain deep learning applications using Java. It provides high-level APIs to help abstract away complex code required for deep learning development.

What is DJL?

Deep Java Library (DJL) is an open-source framework created by AWS to facilitate deep learning development using the Java programming language. Some key aspects of DJL include:

• High-level APIs for building and deploying deep learning models with just a few lines of code. This makes model development faster compared to base frameworks like TensorFlow.
• Model Zoo provides out-of-box access to over 30 pre-trained models including object detection, image classification, text analytics and more.
• Support for multiple engines like PyTorch, MXNet, TensorFlow, helps run models anywhere.
• Model serving functionality to host models and integrate them into applications.
• Supports distributed model training across GPU clusters for faster training.
• Portability of models across different environments and engines.
• Active open source development community.

Overall, DJL aims to make deep learning more approachable to Java developers by reducing boilerplate code and providing high level abstractions. Companies like AWS, IBM, Intel contribute to the DJL project.

DJL Features

Official Links