In this talk we will explore
Microsoft Machine Learning for Apache Spark (MMLSpark), an ecosystem of enhancements that expand the Apache Spark distributed computing library to tackle problems in Deep Learning, Micro-Service Orchestration, Gradient Boosting, Model Interpret-ability, and other areas of modern computation. We also present a novel system called Spark Serving that allows users to run any Apache Spark program as a distributed, sub-millisecond latency web service backed by their existing Spark Cluster. We apply this ecosystem to create deep object detectors capable of learning without human labeled data and demonstrate its effectiveness for Snow Leopard conservation.
