The Oryx open source project provides simple, real-time large-scale machine learning / predictive analytics infrastructure.
The Oryx open source project provides simple, real-time large-scale machine learning / predictive analytics infrastructure. It implements a few classes of algorithm commonly used in business applications: collaborative filtering / recommendation, classification / regression, and clustering. It can continuously build models from a stream of data at large scale using Apache Hadoop. It also serves queries of those models in real-time via an HTTP REST API, and can update models approximately in response to streaming new data. This two-tier design, comprised of the Computation Layer and Serving Layer, respectively, implement a lambda architecture. Models are exchanged in PMML format.
