
Tutorial on Deep Learning - tempw
https://simons.berkeley.edu/talks/tutorial-deep-learning
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mastazi
Because of how my brain works, I have extremely short attention span when
watching videos, but I am much better at reading. The current shift towards
video-only online courses and tutorials worries me greatly.

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gtani
His previous slide decks, which seem to be structured a little differently
(I've only looked for ~5 minutes) are available, so I expect this one will be
too

[http://www.cs.cmu.edu/~rsalakhu/](http://www.cs.cmu.edu/~rsalakhu/)

[http://www.cs.cmu.edu/~rsalakhu/talks/talk_Montreal_part1_pd...](http://www.cs.cmu.edu/~rsalakhu/talks/talk_Montreal_part1_pdf.pdf)

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ttgs
The rest of the talks from this workshop were great as well:
[https://simons.berkeley.edu/workshops/schedule/3748](https://simons.berkeley.edu/workshops/schedule/3748).
These are part of a broader program on foundations of machine learning taking
place this semester:
[https://simons.berkeley.edu/programs/machinelearning2017](https://simons.berkeley.edu/programs/machinelearning2017)

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BonoboBoner
The first eight minutes were promising. Then a mathematical definiton of how
neural networks work follows and I am already lost again when trying to learn
about deep learning. It is like trying to learn Postgresql's new JSON features
by starting to look at relational calculus first.

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argonaut
Not sure why the other comment is being downvoted. You are looking at a talk
given at the Simons Institute for the _Theory of Computing_. I'd be more
worried if there wasn't any math.

If I wanted a newbie intro to operating systems, I would not be looking at
talks at CS conferences like SOSP or OSDI, for example, even if they were
"introductory."

