Deep Learning has become ubiquitous with abundance of data, commoditization of compute and storage. Pre-trained models are readily available for many use-cases.  Distributed Inference has many applications such as pre-computing results offline, backfilling historic data with predictions from state-of-the-art models, etc.,. Inference on large scale datasets comes with many challenges prevalent in distributed data processing. Attendees will learn how to efficiently run deep learning prediction on large data sets, leveraging Apache Spark and Apache MXNet (incubating).

Outline:
Basic Deep Learning Concepts.
Apache MXNet(Incubating) Deep Learning Framework.
Apache Spark Framework
Distributed Inference using Apache MXNet and Apache Spark on Amazon EMR.