PAPIs is the 1st series of international conferences dedicated to real-world Machine Learning applications, and the innovations, techniques and tools that power them.
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the amazon link of the shell:
Garage at 90 degrees
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Totally Spies! HDR settings test (Episode 1 Season 6 Anti Social Network)
I Bought a Fake iPhone Air for €107! Is It as Thin as the Real One?
Teaching A Waiter How To Drift His Car 😂
50 Most Liked Hanime Episodes
Começando na Fotografia? Ñ se preocupe.
Predicting the 2018 Oscar Winners with Machine Learning - Poul Petersen (BigML)
The future of machine learning is decentralized - Alex Ingerman (Google)
DIY Predictive Modeling Cluster with Kubernetes, Dask and JupyterHub - Olivier Grisel (INRIA)
Deep Learning at the edge with AWS DeepLens - Julien Simon (AWS)
Machine Learning, Technical Debt, and You - D. Sculley (Google)
Supercharging Deep Learning with the Unity Engine - Arthur Juliani (Unity)
Automated Machine Learning: Mostly Unhelpful - Charles Parker (BigML)
Scaling Machine Learning as a Service — LI Erran Li (Uber) at #papis2016
A renaissance for decision tree learning — Cynthia Rudin (Duke University) #papis2016
The privacy bounds of human behavior — Yves-Alexandre de Montjoye (MIT & Imperial College)
The emergent opportunity of Big Data for Social Good - Nuria Oliver (Telefonica) #PAPIsConnect
Machine Learning Services Benchmark: choosing the right tools - Inês Almeida #PAPIsConnect