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Artificial Intelligence and Deep Learning

Artificial Intelligence and Deep Learning

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

obrien:obrienlabs amdocs$ docker run -it tensorflow/tensorflow bash Unable to find image 'tensorflow/tensorflow:latest' locally latest: Pulling from tensorflow/tensorflow 22dc81ace0ea: Pull complete 1a8b3c87dba3: Pull complete 91390a1c435a: Pull complete 07844b14977e: Pull complete b78396653dae: Pull complete 22bb9efa20f2: Pull complete e385adcc1f05: Pull complete da0eaa434771: Pull complete