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      $50

      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

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

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