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CS224d: Deep Learning for Natural Language Processing

cs224d.stanford.edu

31–33 of 33 posts

Re: CS224d: Deep Learning for Natural Language Processing

#31

Earlier quoted context omitted.

Where'd you do your undergrad?

I'd rather not bash my undergrad, but suffice to say I tutored intro linear algebra and was very comfortable with eigenvalues, eigenvectors, Gaussian elimination, and that kind of stuff. What was tricky in 224d was taking the gradients with respect to specific components of a matrix. In the end you get comfortable with what the result should look like, but if you actually write the matrix indices down, it's quite hai…

oh yes. thinking in terms of numpy matrix operations while reading the equations took a lot of getting used to.

Re: CS224d: Deep Learning for Natural Language Processing

#32

I was fortunate to take this class the first time it was offered. I found it a great introduction to the material, but a bit over my head. Deep learning requires a strong grasp of linear algebra - and particularly at the "Stanford" level. My undergrad didn't prepare me well for visualizing outer products and matrix / tensor derivatives. Once you get over those hurdles, deep learning is quite fun . It often works like…

Where'd you do your undergrad?

I went to school with Aaron. Zot zot is all I'll say.
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