Presentations

• May 2013 - Survey of Data Science Landscape by Pradeep Gowda
• Sep 2013 - PMML: Generation & Implementation by Jack Xue & Andrew Hoblitzell
• Nov 2013 - A Literature Review on Statistical Models for Healthcare Fraud Detection by Jack Xue & Andrew Hoblitzell
• Dec 2013 - Introduction to iPython by Pradeep Gowda
• Mar 2014 - Presentation on Deep Learning by Andrew Hoblitzell
• Apr 2014 - Presentation on Bayesian Learning by Pradeep Gowda
• Jun 2014 - My First Data Science Project by Pradeep Gowda
• Sep 2014 - Introduction to GPU optimization for Analytic Throughput in R by Matt Gilliam
• Oct 2014 - Preprocessing, Feature Selection, and Cross-Validation: Key Ingredients for a Winning Solution in Kaggle’s DecMeg2014 Competition by Nathan Hammes
• Feb 2015 - News by Andrew Hoblitzell
• Oct 2015 - News by Andrew Hoblitzell
• Nov 2015 - November 2015-Visualization (Part 1), David Taylor
• Dec 2015 - News, Andrew Hoblitzell
• Jan 2016 - R/Caret; Five Tribes of Machine Learning, Andrew Hoblitzell
• Feb 2016 - February 2016-Papers We Love, Pradeep Gowda
• Mar 2016 - Visualization (Part 2), David Taylor
• Apr 2016 - Fishbowl
• May 2016 - Introduction to Mathematical Optimization, Andrew Hoblitzell; Overview of new MOOCs, David Taylor
• Jun 2016 - Support Vector Machines (SVM) presentation, David Taylor
• Jul 2016 - Introduction to TensorFlow, Andrew Hoblitzell
• Aug 2016 - Workshop Preference Optimization, Alexandra Sullivan
• Sep 2016 - Scala for Data Science, Pradeep Gowda