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Comment by _giorgio_ | Hacker News Reader

You can't understand it unless you already know most of the stuff.

I've watched it many times to understand well most of it.

And obviously you must already know pytorch really well, including the matrix multiplication, backpropagation etc. He speaks very fast too...

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Did you really watch all videos in the playlist? I am at video 4 and had no background in PyTorch or numpy.

In my opinion he covers everything needed to understand his lectures. Even broadcasting and multidimensional indexing with numpy.

Also in the first lecture you will implement your own python class for building expressions including backprop with an API modeled after PyTorch.

IMHO it is the second lecture I can recommend without hesitation. The other is Gilbert Strang on linear algebra.

To echo this sentiment, I thought he does a really reasonable job of working up to the topic. Sure, it is fast paced, but it is a video you can rewind, plus play with the notebooks.

There is a lot to learn, but I think he touches on all of the highlights which would give the viewer the tools to have a better understanding if they want to explore the topic in depth.

Plus, I like that the videos are not overly polished. He occasionally makes a minor blunder, which really humanizes the experience.

I was talking about the last video. It's difficult unless you don't know most of the material, or if you havent watched the other videos in the series.

Anyway those videos are quite advanced. Surely not for beginners.

He has like 4 or 5 videos that can be watched before that one where all of that is covered. He goes over stuff like writing back prop from scratch and implementing layers without torch.

I know... That material isn't for beginners.

...but then, what material did you expect as a beginner?

How can Karpathy videos defined for beginners when you have to know: programming, python, pytorch, matrix multiplication, derivatives...

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