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dimodimi

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There's this fast.ai course I found a while ago. I haven't gone through it yet but it should be relevant to this chapter and to the whole of part 1 (it touches on some machine learning tools like Stochastic Gradient Descent, PCA, linear regression). The course consists of videos accompanied by jupyter notebooks.

The site also offers two deep learning courses, so you might want to keep it bookmarked during the whole study period. Just go to the homepage and they should be at the top (Practical Deep Learning for Coders and Cutting Edge Deep Learning for Coders).

Just a note, the course seems to use pytorch and scikit-learn so you'll have to put some extra work getting familiar with the tools.

Anyway, here's the link: Computational Linear Algebra
and the fast.ai site: fast.ai

PS: I remember doing the introductory NN training a while ago and I think it involved the plain MNIST dataset. I was gonna skip but it seems like they changed it to Fashion MNIST. Was it always like this?

I would like to join as well, thanks!

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