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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