quarterly msug meeting linda vance · presented a use case that covered supervised machine learning...

14
Quarterly MSUG Meeting Linda Vance

Upload: others

Post on 26-May-2020

4 views

Category:

Documents


0 download

TRANSCRIPT

Page 1: Quarterly MSUG Meeting Linda Vance · Presented a use case that covered supervised machine learning using the Bayesian Network Classifier Node Effectively Fighting Fraud –Constantine

Quarterly MSUG Meeting

Linda Vance

Page 2: Quarterly MSUG Meeting Linda Vance · Presented a use case that covered supervised machine learning using the Bayesian Network Classifier Node Effectively Fighting Fraud –Constantine

When & where…

❖ September 18 – 20, 2017

❖ Washington DC

❖ Gaylord National Resort & Convention Center❖National Harbor, MD

Cool App to use on your phone

to have the conference info at

your fingertips!

Page 3: Quarterly MSUG Meeting Linda Vance · Presented a use case that covered supervised machine learning using the Bayesian Network Classifier Node Effectively Fighting Fraud –Constantine

Keynote Speakers

❖ Navigating Change in the Analytics Economy ❖ Jim Goodnight, CEO, SAS❖ Oliver Schabenberger, EVP & Chief Tech Officer, SAS❖ Shawn Hushman, VP of Decision Sciences, Cox Automotive❖ Chris Donovan, Enterprise Information Mgmt. & Analytics

❖ How Technology & Innovative Approaches Can Transform Your Organization❖ Megan Smith, Innovative Tech Leader & Former US Chief

Technology Officer

Day One…

Page 4: Quarterly MSUG Meeting Linda Vance · Presented a use case that covered supervised machine learning using the Bayesian Network Classifier Node Effectively Fighting Fraud –Constantine

Keynote Speakers

❖ Closing the Gender Gap in Technology❖Reshma Saujani, Founder & CEO of Girls Who Code & Author

❖ Taking Advantage of Technology Disruption❖ D.J. Patil, Former Chief Data Scientist of the United States❖ Tom Davenport, President’s Distinguished Prof. of Information

Technology & Management, Babson College❖ Oliver Schabenberger, EVP & Chief Technology Officer, SAS

❖ Artificial Intelligence❖ Machine Learning

Day Two…

Page 5: Quarterly MSUG Meeting Linda Vance · Presented a use case that covered supervised machine learning using the Bayesian Network Classifier Node Effectively Fighting Fraud –Constantine

Keynote Speakers❖ Analytics at the Edge: Bringing Intelligence to the IoT

❖Garret T. Fitzgerald, GM, Transport Intelligence, GE Transportation Digital Solutions

❖Randy Guard, EVP & Chief Marketing Officer, SAS

❖ A Conversation With Earvin “Magic” Johnson❖ Chairman & CEO, Magic Johnson Enterprises

❖ One of the leading investors in a number of minority-owned tech companies❖ Unchartered Play❖ ShotTracker❖ Jopwell❖ Walker & Co Brands❖ MiTú

Day Three…

Page 6: Quarterly MSUG Meeting Linda Vance · Presented a use case that covered supervised machine learning using the Bayesian Network Classifier Node Effectively Fighting Fraud –Constantine

SAS News❖ Release 9.4 M5 is now available

❖ Enables customers to use the functionality in SAS Viya

❖ Many functions have been enhanced to take advantage of the fast, distributed processing provided by Cloud Analytic Services, which is part of SAS Viya

❖ Includes enhancements in creating accessible output, programming and accessing data, and using TLS (Transport Layer Security) protocols for more secure deployment options.

❖Several SAS analytical products, including SAS/ETS, SAS/STAT, and SAS Enterprise Miner, shipped a new release.

Page 7: Quarterly MSUG Meeting Linda Vance · Presented a use case that covered supervised machine learning using the Bayesian Network Classifier Node Effectively Fighting Fraud –Constantine

Hot Topics…

https://www.sas.com/offices/pdf/be/2017-sas-forum-belux/plenary/the-future-of-the-sas-platform-mike-frost.pdf

Page 8: Quarterly MSUG Meeting Linda Vance · Presented a use case that covered supervised machine learning using the Bayesian Network Classifier Node Effectively Fighting Fraud –Constantine

Session Opportunities…❖Innovation Hub

❖Theater Sessions

❖ Super Demos

❖ Table Talks

❖ Posters

There were approximately 78

different Innovation Hub

sessions to choose from!

Page 9: Quarterly MSUG Meeting Linda Vance · Presented a use case that covered supervised machine learning using the Bayesian Network Classifier Node Effectively Fighting Fraud –Constantine

Breakout Sessions

❖ Making Analytics Pervasive – Saurabh Gupta & Udo Sglavo, SAS❖New release- Unified BI & Analytics capabilities

❖ I’ll Take Science Wrapped in a Narrative with a Side of Data, Please❖ Bree Baich, SAS Best Practices❖ How to communicate complex concepts through data

storytelling

❖ Demystifying the intersection Between Financial Crime Risk & Machine Learning – Nikhil Aggarwal, Fintech Entrepreneur❖ Event Optimization

❖ How to Win Friends & Influence Executives: A Guide to Getting your Point Across – David Harcourt, Yum! Brands Inc.

There were approximately 62

different Breakout sessions to

choose from! Here are just a

few…

Page 10: Quarterly MSUG Meeting Linda Vance · Presented a use case that covered supervised machine learning using the Bayesian Network Classifier Node Effectively Fighting Fraud –Constantine

Breakout Sessions

❖ Surveillance Bot: an Automated Classification Pipeline for Fraud Detection – Wayne Thompson & Yue Qi, SAS❖Bot specially designed for fraud detection addresses the

common case of unbalanced data, feature engineering & champion challenger model selection.

❖ Bayesian Network Classifier Model Using SAS Enterprise Miner, Anurag Mhaiskar, SAS ❖ Overview of the Bayesian Network Model in SAS❖ Presented a use case that covered supervised machine learning

using the Bayesian Network Classifier Node

❖ Effectively Fighting Fraud – Constantine Boyadjiev, Accenture❖ Surveillance analytics, social network analysis, & deep

emotion/sentiment analysis in misconduct & behavioral risk.

There were approximately 62

different Breakout sessions to

choose from! Here are just a

few…

Page 11: Quarterly MSUG Meeting Linda Vance · Presented a use case that covered supervised machine learning using the Bayesian Network Classifier Node Effectively Fighting Fraud –Constantine

Hands-On Workshops❖ Python Integration With SAS Viya, Marc Huber, SAS

❖ CAS – Cloud Analytic Services❖ Jupyter Notebook❖ SWAT – interface to the CAS engine

❖ R Integration With SAS Viya, Robert Blanchard, SAS❖ Connect to CAS Server – rpy2 package❖ Analyze large in-memory data sets❖ Work with the results data wrangling techniques with R

❖ SAS Visual Data Mining and Machine Learning, Andy Ravenna, SAS❖ SAS Viya❖ Build supervised models & evaluate the results of analysis

through an interactive, web-based & visual interface

Page 12: Quarterly MSUG Meeting Linda Vance · Presented a use case that covered supervised machine learning using the Bayesian Network Classifier Node Effectively Fighting Fraud –Constantine

And of course… Food & Fun…❖ Airplanes to Astronauts: A Night at the Museum

❖ National Air and Space Museum

❖ Dinner, drinks and dessert

❖ Entertainment – Live Band

And let’s not forget…

there was some SWAG

too!

Page 13: Quarterly MSUG Meeting Linda Vance · Presented a use case that covered supervised machine learning using the Bayesian Network Classifier Node Effectively Fighting Fraud –Constantine

And of course… Food & Fun…❖ Monuments by Moonlight Tour

❖ Bus tour of the monuments

❖ Stop off at the Lincoln Memorial to get photos

Page 14: Quarterly MSUG Meeting Linda Vance · Presented a use case that covered supervised machine learning using the Bayesian Network Classifier Node Effectively Fighting Fraud –Constantine

Manchester Grand HyattSan Diego

September 17 – 19, 2018