BAM - Scaling Computer Vision, and NLP and Advanced Text Analytics

NLP and Advanced Text Analytics Implementation
Presented by Stanley J. Mlynarczyk, Ph.D. - Pandata Group

We will explore the basics of text analytics and Natural Language Processing and then focus on application of these techniques to question answering. Topics covered will include: word frequency, parsing of sentences, part of speech tagging, use of an ontonomy, phrase analysis and resolution, synonomy and pattern matching. Question answering is particularly interesting in today's world of Amazon, IBM Watson, Echo and Siri. The presentation will show how these tools achieve their functionality and where they need to go to improve. A secondary goal for the presentation will be to show how this functionality can be utilized by the business community at large. Links to useful tools will be provided.

Scaling Computer Vision Workloads with Pub/Sub Messaging and Docker
Presented by Brad Hoskins, MapR

Computer vision technology has exploded in popularity since the models such as InceptionNet and ImageNet were published. In this presentation, Brad will take us through computer vision applications, scaling recommendations, and a demonstration of scaling using containers, GPUs, and MapR Streams.