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5 - Technical [clear filter]
Monday, December 3

9:30am CST

The Road Ahead: Artificial Intelligence, Machine Learning, Data Analytics, and Visualization
Professor Dan Aierly (Duke University) has been quoted saying, “Big data is like teenage sex: everyone talks about it, nobody really knows how to do it, everyone thinks everyone else is doing it, so everyone claims they are doing it...” Dr. Bonnie Holub will discuss working examples of how some of the 12 million worldwide Teradata users who are processing  $10 trillion dollars’ worth of revenue in 11 trillion annual queries into just under one zettabyte of data. She will cover hyper-segmentation of large data sets, fraud detection, preventive maintenance and techniques working systems employ to dig deep,  aim high and manage operations at scale.

avatar for Bonnie Holub

Bonnie Holub

Director & Principal Data Scientist, Teradata
Bonnie Holub, Ph. D.  leads Data Science in the Midwest GEO as a Teradata Consulting Principal Data Scientist. Bonnie holds a PhD in Artificial Intelligence and has served a variety of roles including: VP Talent Analytics at Korn Ferry, Master Data Scientist at Cognizant, Analytics... Read More →

Monday December 3, 2018 9:30am - 10:15am CST
(3) Discovery Hall (Floor 4) Science Museum of Minnesota, 120 W Kellogg Blvd St. Paul, MN 55102

1:00pm CST

Helping the Data Scientist deploy code from end to end in Azure
Demonstration on how to enable a data scientist to take a model from code to a Kubernetes cluster in Azure using AutoML and Azure Machine Learning Service.

avatar for Huy Ly

Huy Ly

Cloud Solution Architect, Microsoft

Monday December 3, 2018 1:00pm - 1:45pm CST
(3) Discovery Hall (Floor 4) Science Museum of Minnesota, 120 W Kellogg Blvd St. Paul, MN 55102

2:00pm CST

Reducing False Positives in Transactions with Deep Fraud Detection
Fraud is a critical issue in financial services, at an estimated $15-25 Billion size for the industry in 2017. Fraud detection and management has typically been performed using a combination of business rules and traditional machine learning. However, such solutions invariably generate a large number of costly false positives. We will present a solution architecture that combines automated machine learning, deep feature synthesis and streaming analytics to power a scalable, deployable deep fraud detection system.

avatar for Anshuman Mishra

Anshuman Mishra

Principal Data Scientist, Tibco Software, Inc.

Monday December 3, 2018 2:00pm - 2:30pm CST
(6) Xenon Room (Floor 6) Science Museum of Minnesota, 120 W Kellogg Blvd St. Paul, MN 55102