Theories of Deep Learning (STATS 385) by stats385


27 bookmarks. First posted by zub 14 days ago.


Nice reference for deep learning. Seems to have clear and concise cheat sheets.
DL  course 
12 days ago by gideonite
The spectacular recent successes of deep learning are purely empirical. Nevertheless intellectuals always try to explain important developments theoretically. via Pocket
Pocket 
13 days ago by LaptopHeaven
Stanford University, Fall 2017 The spectacular recent successes of deep learning are purely empirical. Nevertheless intellectuals always try to explain…
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14 days ago by matttrent
Stats 385 course website
14 days ago by phutwo
Stanford lecture course STATS 385
learning  artificialintelligence  tutorial 
14 days ago by MrStimpson
The spectacular recent successes of deep learning are purely empirical. Nevertheless intellectuals always try to explain important developments theoretically. In this literature course we will review recent work of Bruna and Mallat, Mhaskar and Poggio, Papyan and Elad, Bolcskei and co-authors, Baraniuk and co-authors, and others, seeking to build theoretical frameworks deriving deep networks as consequences. After initial background lectures, we will have some of the authors presenting lectures on specific papers. This course meets once weekly.
statistics  DeepLearning  machine-learning  Stanford  course  programming 
14 days ago by dangeranger
Stats 385 course website
deeplearning 
14 days ago by geetarista
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HNews: Stanford Stats 385: Theories of Deep Learning https://t.co/DAwOd9R9Rs

— Tech news (BOT) (@tek_news) November 7, 2017

http://twitter.com/tek_news/status/927952562480975872
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14 days ago by tswaterman
Stanford Stats 385: Theories of Deep Learning (cmts )
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14 days ago by rukku