Deploying Keras Deep Learning Models with Java – Towards Data Science

The Keras library provides an approachable interface to deep learning, making neural networks accessible to a broad audience. However, one of the challenges I've faced is transitioning from exploring models in Keras to productizing models. Keras is written in Python, and until recently had limited support outside of these languages. While tools such as Flask, PySpark, and Cloud ML make it possible to productize these models directly in Python, I usually prefer Java for deploying models. Projects such as ONNX are moving towards standardization of deep learning, but the runtimes that support these formats are still limited.