PAPIs '16 Presentations Access — 3rd International Conference on Predictive Applications and APIs

Couldn't attend PAPIs '16? Get access to the presentations' slides, videos, and get early access to the proceedings (coming soon — papers are being reviewed)!

Slides:

• A multi-pronged approach to speeding up predictive applications - Scott Leishman (Nervana)
  
• Accelerating Model Development and Deployment with the right API - Dallin Akagi (DataRobot)
  
• Beyond Churn Prediction - An Introduction to Uplift Modelling - Pierre Gutierrez (Dataiku)
  
• Cynthia Rudin (Duke)
  
• Deep Neural Networks in Azure - Anusua Trivedi (Microsoft)
  
• Deploying Python Models as an API - Henri Dwyer (Dataiku)
  
• End to end Machine Learning using mldb.ai - Jeremy Barnes (mldb)
  
• Enterprise API Security for Machine Learning Predictive APIs - Jason Macy (Forum Systems)
  
• Evaluating Failure Prediction Models for Predictive Maintenance - Shaheen Gauher (Microsoft)
  
• Patient Health Condition Prediction and Monitoring - Yan Zhang (Microsoft)
  
• Predict what color of shoes your customer wants to buy next - Bas Nieland (Datatrics)
  
• Predicting Customer Behavior - Vinny Senguttuvan (Metis)
  
• Predicting Power of Emotions - Lana Novikova & Lisa Lewers
  
• Prediction | Production - Lessons from Over-the-wall - Stu Bailey (ODG)
  
• Scaling Machine Learning as a Service at Uber - Li Erran Li (Uber)
  
• Spark for Data Analysts - Clement Stenac (Dataiku)
  
• The Smarts in Smart Home Health - Sean Lorenz (Senter)
  
• Using Recommendation Systems to find the bad guys - Arjun Chakraborty (The Home Depot) 
  

Videos:

• Patient Health Condition Prediction and Monitoring — Yan Zhang (Microsoft)
  
• Bringing the power of Spark to all data analysts — Clément Stenac (Dataiku)
  
• When all the world's data scientists are just not enough — Chalenge Masekera (Salesforce)
  
• Interpretability — Cynthia Rudin (closing Keynote day 1)
  
• Regulating Greed Over Time— Cynthia Rudin (Duke & MIT)
  
• [Tutorial] Beyond Churn Prediction: An Introduction to Uplift Modelling — Pierre Gutierrez (Dataiku)
  
• Scaling Machine Learning as a Service — LI Erran Li (Uber)
  
• Transfer Learning & Fine-tuning Deep Convolution Neural Network model — Anusua Trivedi
  
• The privacy bounds of human behavior — Yves-Alexandre de Montjoye (MIT Media Lab)
  

More info on the conference and talk abstracts at papis.io/2016