A scalable Keras deep learning REST API - PyImageSearch

In today's blog post we are going to create a deep learning REST API that wraps a Keras model in an efficient, scalable manner. Our Keras deep learning REST API will be capable of batch processing images, scaling to multiple machines (including multiple web servers and Redis instances), and round-robin scheduling when placed behind a load balancer. For a more simple Keras deep learning REST API, please refer to this guest post I did on the official Keras.io To learn how to create your own scalable Keras deep learning REST API, just keep reading! Today's tutorial is broken into multiple parts. We'll start with a brief discussion of the Redis data store and how it can be used to facilitate message queuing and message brokering.