The Future of Deep Learning Research

Back-propagation is fundamental to deep learning. Hinton (the inventor) recently said we should "throw it all away and start over". What should we do? I'll describe how back-propagation works, how its used in deep learning, then give 7 interesting research directions that could overtake back-propagation in the near term.

Code for this video:
https://github.com/llSourcell/7_Research_Directions_Deep_Learning

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More learning resources:
https://www.youtube.com/watch?v=q555kfIFUCM
https://www.youtube.com/watch?v=h3l4qz76JhQ
https://www.youtube.com/watch?v=vOppzHpvTiQ
https://deeplearning4j.org/deepautoencoder
https://deeplearning4j.org/glossary
https://www.reddit.com/r/MachineLearning/comments/70e4ex/n_hinton_says_we_should_scrap_back_propagation/
https://mattmazur.com/2015/03/17/a-step-by-step-backpropagation-example/
http://kvfrans.com/generative-adversial-networks-explained/

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Видео The Future of Deep Learning Research канала Siraj Raval