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This is a particular unique course offering introduction on ML compilation and deployment :)


I really liked the style of the instructor (Kolter), and the reason I like this course very much is because each lecture is followed by an implementation video along with the notebook file.

In most Deep Learning courses, the implementation is left to TAs and neither recorded nor made available. This course is an exception. Another bright exception is NYU Deep Learning course [0] by Yann LeCun and Alfredo Canziani. In that course, too, all recitations ("Practica") are recorded and made available. And Canziani is a great teacher.

[0]: https://atcold.github.io/pytorch-Deep-Learning


I also really like the instructor for this course!

Seems like he really cares. I looked him up and I guess he was a student of Andrew Ng (the legendary ML lecturer!!) so it makes sense.


Thanks, this is a wonderful recommendation




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