Deep Learning: Theory, Practice and Predictions!

Expect spikes from both the artificial & natural neurons!! In this talk, Arno Candel, Physicist & Hacker at H2O.ai will breakdown the basics of deep learning in theory & present implementation, early results from using MLP with Adaptive learning as implemented in H2O. Some recognizable datasets such as mnist and industrial datasets will find their solutions in this powerful modeling technique. Outside of Theano, Netflix, baidu and Google this is one of the top parallel and distributed implementation of Deep Learning.

Prior to joining 0xdata as Physicist & Hacker, Arno was a founding Senior MTS at Skytree where he designed and implemented high-performance machine learning algorithms. He has over a decade of experience in HPC with C++/MPI and had access to the world's largest supercomputers as a Staff Scientist at SLAC National Accelerator Laboratory where he participated in US DOE scientific computing initiatives. While at SLAC, he authored the first curvilinear finite-element simulation code for space-charge dominated relativistic free electrons and scaled it to thousands of compute nodes.

He also led a collaboration with CERN to model the electromagnetic performance of CLIC, a ginormous e+e- collider and potential successor of LHC. Arno has authored dozens of scientific papers and was a sought-after academic conference speaker. He holds a PhD and Masters summa cum laude in Physics from ETH Zurich.