Want to get your hands dirty with Machine Learning / Deep Learning, but have a Java background and not sure where to start? Then read on! This article is about using an existing Java skillset and ramp-up your journey to start building deep learning models.

What is DJL?

DJL is an open-source library to build and deploy deep learning in Java. DJL is built by AWS and is open source.

DJL provides a native Java development experience and functions like any other regular Java library & expedite machine learning and deep learning journey. Developers can use their existing IDE (Eclipse/ IntelliJ) to build, train and deploy models and DJL makes it easy to integrate these models with Java Apps.

The simple APIs abstract away the complexity involved in developing Deep learning models. With the bundled set of pre-trained models from ModelZoo, users can immediately start integrating Deep learning into their Java applications.

DJL is engine-agnostic and goes with Java fundamental “Write once, run anywhere”. A developer can develop a model using DJL and run it on an engine of your choice - MXNet, Pytorch, TensorFlow.

DJL Example for Object Detection

Object detection is a computer vision technique for locating instances of objects in images or videos.

In this example, we will learn how to implement inference code with a ModelZoo model to detect dogs in an image. Source code for this model is here.

#open-source #aws #tech #deep-learning #java #digital-transformation #cloud-computing #agile-mindset