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Personally I recommend Stanford CSI 231n http://cs231n.stanford.edu/

Its specifically geared towards visual recognition, but it starts with the basics of machine learning and moves on to feed forward nets and covnets and covers RNNs and attention towards the end.

The assignments are a great set of jupyter notebooks that really get your hands on the material and you can find a number of peoples complete assignments on github just by searching.

The lectures are available online as well https://www.youtube.com/playlist?list=PL3FW7Lu3i5JvHM8ljYj-z...

I've done hinton's and Ngs courses and as someone who already has a non-ai development background I found this to be the best introduction. Its really an extension of Andrej Karpathy's Neural Nets for Hackers (http://karpathy.github.io/neuralnets/)




Did you signup for the course, or just followed what's available on the page? It doesn't seem like there is any starting date there.




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