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> Why do we have to write the backward pass when frameworks in the real world, such as TensorFlow, compute them for you automatically?

Why do you have to learn to calculate integrals and derivatives in school, or how compilers work internally? Same answer. But seriously, the CS231 class is excellent, and Andrej is an excellent teacher. You can follow along at home (which is what I am doing.) The syllabus (at http://cs231n.stanford.edu/syllabus.html) has the course notes and the assignments. The assignments are self grading, you know when you have it programmed correctly. The lectures are here: https://www.youtube.com/playlist?list=PLlJy-eBtNFt6EuMxFYRiN...

Sort of off topic. I have been planning to do the same course(CS 231n), and was wondering, is it okay if I do the Andrew Ng Machine Learning (Coursera) in parallel, or is it more of a prerequisite ?

I only did the first several videos of Andrew Ng's class, and didn't like it. The only prerequisites to CS231n are linear algebra, calculus, and Python.

As long as you know a lil bit of math and coding, you're good to go. If you're watching the cs231n videos and don't understand something, you can always check out their amazing class notes.

The cs231n course covers a lot of material, including some (or most) of the material from the Andrew Ng's Coursera course. You can totally do them in parallel though.

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