Toronto Data Sciences Forum
The Data Sciences Forum is an opportunity for you to explore data science related issues, share ideas and discuss industry standards and trends with your peers. Each session will explore current trends, new technology and data science techniques through presentations and discussion sessions. As always, these meetings are free to attend.
The next Data Sciences Forum will take place Wednesday, May 17, 2017 at the SAS Canada offices (5th Floor, 280 King St East). A detailed agenda is currently in development and will be made available as soon as possible.
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Random Forests: Basics and Advantages: Antoni Dzieciolowski, SAS Canada (November 2016)
Big Data, Big Headaches: An Agile Modeling Solution Designed for the Information Age: Meriam Seirafi, Cornerstone Group of Companies (November 2016)
SAS and Open Source: Matt Malczewski, SAS Canada (November 2016)
Customer Credit and Pricing Optimization: Yuri Medvedev, Bank of Montreal (May 2016)
Methodologies of LGD Confidence Interval Calculation: Cathy Bei Li, CIBC (May 2016)
Open Source and SAS: Pat Valente, SAS Canada (May 2016)
Update from SAS: Warren Woermke, SAS Canada (November 2015)
How to Positively Affect ROI through Effective Marketing: Joanna Carbajal, Sandbox (November 2015)
Real-Time Analytics: Myths, Tactics & Level-Setting: Tim Trussell, SAS Canada (November 2015)
Predictive Model Robustness Validation: Charles Chen, TD Bank Financial Group (November 2015)
Statistics and Social Issues: Joyce Chen, IMS Health (November 2015)
Transforming Web/Digital Data to Customer Information: Cory Narvaez, Scotiabank (November 2015)
News from SAS: Matt Malczewski, SAS Canada (May 2015)
Product Recommender System in Retail: (Pramod Dogra & Iqbal Habib, Shoppers Drug Mart (May 2015)
SAS Enterprise Miner for Non-Traditional Targets: A Look at Survival Modeling, Net Lift and Time Series Similarity Analysis (May 2015)
B2B Sales Analytics: What Activities in Your Sales Cycle are Winning Business?: John Amrhein, McDougall Scientific Ltd. (May 2015)
Introduction to Ensemble Learning in Credit Risk Modelling: Han Sheng Sun, BMO & Zi Jin, Wells Fargo (October 2014)
Update from SAS: Matt Malczewski, SAS Canada (October 2014)
The Use of Data in Commercial Lines: Dahchour, Scarth & McGee Northbridge (May 2014)
Reject Inference for Credit Adjudication: van Berkel BMO (May 2014)
Logistic Regression Model: Jiarui Dang (October 2013)
Scoring Models, Probability Transformations & Model Calibration: Benamara, Dzieciolowski Rogers (October 2013)
SAS EM Code Node Tips: Lorne Rothman SAS Institute (October 2013)
SAS Visual Analytics: Trussell SAS Institute (May 2013)
Pricing Optimization Unsecured Lending: Jane Zhong Scotiabank (May 2013)
Survival Model and Attrition Analysis: Charles Chen, TD Canada Trust (March 2012)
Data Quality Assurance: Mahmoud Azimaee, University of Manitoba (2012)
Computer Resource Usage in Data Mining: Masoud Charkhabi, CIBC (May 2012)
Modeling Interaction Effects in Linear and Generalized Linear Models: Timothy Gravelle, PriceMetrix Inc. (Fall 2012)
Survival Data Mining in SAS EM: Lorne Rothman (Fall 2012)
Experimental Design Techniques: Saaramaki (May 2012)
SAS Text Analytics: Tim Trussell, SAS Canada Inc. (Fall 2012)
Philosophy and Practice in Fraud Detection Analysis: Mario Wen (May 2012)
Practical Data Governance Use: Alex Salvas, National Bank (October 2011)
Segmentation Do's and Don'ts: Daymond Ling, CIBC (October 2011)
Scenario and Stress Testing Using SAS/IML: Dimitry Donin, Dmytro Koral & Mykola Tkachenko, BMO (April 2011)
The Curious Complications of Confounding Covariates: Derek de Montriachard, CIBC (Fall 2011)
Banking Credit Risk Data Quality Control: Mark An, CIBC (May 2010)
SAS in Social Media: Matt Malczewski, SAS Canada Inc. (Fall 2010)
Social Network Analysis: Dan McKenzie (May 2010)
Create the Most Powerful CRM System (in 1996): Ray Kong, Ipsos Reid Corporation (May 2010)
Net Lift and Return Maximization: Victor Zurkowski, CIBC (Fall 2010)
Spline Modeling for Non-Linear Trends: Derek Montrichard, CIBC (May 2009)
Ensuring Model Performance: Gene Jigota, TSBC Consulting (October 2009)
An Elasticity Similarity Distance & Application: Kelvin Li, CIBC (September 2009)
Data Expansion in Credit Risk Modeling: Mark An CIBC (May 2009)
Data Mining in Business Analytics for Decision Support: Albert He, Scotiabank
Web Analytics Full Circle - Back to the Data Mine: Christopher Berry, Critical Mass
Predictive Modeling in Retail: Jim Godfrey, SAS Canada Inc.
Comparing Different Classification Techniques in Credit Scoring: Saed Sayad, iSmartsoft
Improve Marketing Campaign Using Uplift Modeling: Ryan Zhao, Analytic Resourcing Centre
Challenge of Variable Reduction in External Acquisition Modeling: Mariam Seirafi, Cornerstone Group