Developers should be prepared to integrate with and use their deep learning portfolio.  Before we get some scope on their API's and endpoints some background in deep learning (a specialized subset of machine learning concentrated on the "Greedy Layer-Wise Unsupervised Pretraining procedure" - Hinton, 2006 - University of Toronto) and the "Long Short-Term Memory model - Hochreiter and Schmidhuber 1997" will be required.

JIRAs

LOG-500: Machine Learning on ONAP Logs - streamed and bulk ML processingClosed

LOG-511: AWS Machine Learning RI for ONAP LogsClosed

LOG-104: Investigate Jaeger / opentracing / zipkin distributed tracing agent/serverClosed

Design/Theory Preparation

Get the following Nov 2016 MIT book from Amazon by Ian Goodfellow, Yoshua Benglo, Aaron Courville - (one for work, and one for home - as it is usually out of stock).  Review your linear transformation and matrix math to prep.

https://www.amazon.ca/Deep-Learning-Ian-Goodfellow/dp/0262035618/ref=sr_1_1?ie=UTF8&qid=1486501444&sr=8-1&keywords=deep+learning

https://developers.google.com/machine-learning/crash-course/

Installing Tensorflow

follow/verify via https://www.tensorflow.org/install/install_mac