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model deployment

19 papers and 11 presentations; 28 titles.

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Conference × Year × Title × Authors Extras Pages
PHUSE EU 2024 Responsible AI in Protocol Design for Use in Digital Data Flow Alistair Dootson,
Poorya Amini		 source
presentation source		 4
WUSS 2023 Leveraging Teradata ClearScape Analytics to Improve ROI [presentation] Gregory Goralski,
Paul Segal		 source 40
SAS Explore 2022 SAS Analytics in Microsoft Azure - AI Has Never Been Easier! [video] Rich Main source
youtube
PHUSE EU 2020 Patient Insights and Real-world Data from Social Media [presentation] Luisa Regenold,
Soundarya Palanisamy		 source
video		 28
SGF 2019 The Aftermath What Happens after you Deploy Your Models and Decisions David R. Duling source 18
SGF 2018 Navigating the Analytics Life Cycle with SAS Visual Data Mining and Machine Learning Susan Haller,
Brett Wujek		 source 29
SGF 2017 Shipping Container Roulette [presentation] Dan Tamburro source 29
SGF 2016 Analytics and Data Management in a Box: Dramatically Increase Performance Greg Otto,
Tho H. Nguyen,
Paul Segal		 source 14
SGF 2016 Mass-Scale, Automated Machine Learning and Model Deployment Using SAS Factory Miner and SAS Decision Manager Jonathan Wexler,
Steve Sparano		 source 19
SGF 2013 Time Is Precious, So Are Your Models: SAS Provides Solutions to Streamline Deployment Jonathan Wexler,
Wayne Thompson		 source 17
SGF 2012 How Does SAS In-Database Analytics Impact Data Management? Adrian Jones source 8
SGF 2011 Creating a SAS Model Factory Using In-Database Analytics John Spooner source 8
SGF 2009 The Next Generation: SAS Enterprise Miner 6.1 David R. Duling,
Wayne Thompson		 source 10
PharmaSUG 2008 From Soup to Nuts: Practices in Data Management for Analytical Performance David R. Duling 25
SGF 2008 From Soup to Nuts: Practices in Data Management for Analytical Performance David R. Duling,
Howard Plemmons Jr.,
Nancy A. Rausch		 source 24
MWSUG 2007 Best Practices for Managing Predictive Models in a Production Environment Robert Chu 10
SGF 2007 Best Practices for Managing Predictive Models in a Production Environment Robert Duling,
David M. Thompson,
Wayne Chu		 source 10
SGF 2007 Variable Screening for Multinomial Logistic Regression on Very Large Data Sets as Applied to Direct Response Modeling John A. Cherrie source 12
NESUG 2006 Predicting Child Support Payment Delinquency Using SAS Enterprise Miner 5.1 Jodi Blomberg,
Jacqueline K. Long		 12
SUGI 2006 Predicting Child Support Payment Delinquency Using SAS Enterprise Miner 5.1 Jodi Blomberg,
Jacqueline K. Long		 source 12
SEUGI 2003 SAS Credit Scoring In-House Scorecard Development Project [presentation] Helena Junqueiro,
Henrik Wagner		 source 40
SEUGI 2002 Data Mining In A Zero Latency Enterprise Environment [presentation] Luca Selvatici source 24
SEUGI 2001 Building a compelling case for Enterprise Miner Within The Bank of Scotland [presentation] Simon Hughes source 33
SEUGI 2001 Data Mining In a Zero Latency Enterprise [presentation] Philip Bosinoff source 36
SEUGI 2001 New Features and Future Directions for Enterprise Miner [presentation] David R. Duling,
Gerhard Held		 source 31
SEUGI 2001 The Intelligence Layer - an Organized Approach to Business Intelligence [presentation] Allan Russell,
Stefan Gossler		 source 57
SUGI 2000 Production-Strength Data Mining Environment for Terabyte-Class Relational Data Warehouses Michael K. Nichols,
John Zhao,
John David Campbell		 source
SESUG 1999 Tessera Rapid Modeling Environment: Production-Strength Data Mining Solution for Terabyte-Class Relational Data Warehouses Michael Nichols,
John Zhao,
John David Campbell		 source 9
SEUGI 1999 Data warehouse architecture for model development [presentation] David Annis,
Turlough Fitzpatrick		 source 32
SUGI 1998 A Data Access Challenge: Build a SAS Frame Application for Access to an Informix Data Warehouse John E. Bentley source 7

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