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Deep Learning has become an essential toolbox which is used in a wide variety of applications, research labs, industry, etc. In this tutorial, we will provide a set of guidelines which will help newcomers to the field understand the most recent and advanced models, their application to diverse data modalities (such as images, videos, waveforms, sequences, graphs,) and to complex tasks (such as learning to learn from a few examples, or generating molecules).
Author Information
Nando de Freitas (DeepMind)
Scott Reed (Google DeepMind)
Oriol Vinyals (Google DeepMind)
Oriol Vinyals is a Research Scientist at Google. He works in deep learning with the Google Brain team. Oriol holds a Ph.D. in EECS from University of California, Berkeley, and a Masters degree from University of California, San Diego. He is a recipient of the 2011 Microsoft Research PhD Fellowship. He was an early adopter of the new deep learning wave at Berkeley, and in his thesis he focused on non-convex optimization and recurrent neural networks. At Google Brain he continues working on his areas of interest, which include artificial intelligence, with particular emphasis on machine learning, language, and vision.
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