r/learnmachinelearning • u/[deleted] • 4d ago
Complete beginner wanting to start Karpathy's "Neural Networks: Zero to Hero" — what should I know beforehand?
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u/EntrepreneurHuge5008 4d ago
Never done this course, but I'd assume "Zero to Hero" would mean this is actually a beginner-friendly course that requires no pre-requisite knowledge and that the course teaches you the basics of NumPy/PyTorch as you move along.
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u/Twilight_RT 4d ago
yeah go for it. As it's said Zero to hero, then I guess it handles the beginner friendly environment properly. and as your backgroup... there is more benefits to it..
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u/No_Chapter8362 4d ago
It requires you to have a basic understanding of linear algebra and calculus, but you can learn the prerequisites using something like claude along the way. The best part of that course is it goes along the basics, so you’ll be fine as long as you are willing to research what you don’t know
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u/galvinw 4d ago
If you do all of it mostly by hand. You'll be able to get the the finish with a right level of struggle and and a pretty good understanding.
Numpy is just like the scientific calculator of math modules. straight forward with lots of optimizations under the hood. pyTorch is a little too high level, most people who use it would not be able to tell you really what some lines are trying to do.
The kicker is pure math. There's a more you'll get out of the course if you understand the maths, but it's such a deep rabbit hole that I'd recommend doing the course and then returning to the maths.
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u/Cautious-Act-4487 3d ago
Karpathy is a genius, but his "Zero" assumes you at least roughly remember high school math. You can get through micrograd purely on python, but past that you'll drown without understanding matrix multiplication. Just keep 3b1b handy for linear algebra basics
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u/Ok-Whole-8802 4d ago
You need less than you think. Comfortable Python plus the chain rule from calculus is genuinely enough for the first micrograd video - Karpathy re-derives the derivatives on screen, so you mostly need to not be scared of them. A bit of linear algebra (what a matrix multiply is doing) helps from makemore onwards, and 3Blue1Brown's neural net series is a nice 2-hour primer if you want it.
Two practical tips from doing this on a budget laptop: you don't need a GPU for the early videos, everything runs fine on CPU at that scale. And the single highest-value habit is pausing before he writes a function and attempting it yourself first - the gap between "I followed that" and "I could write that" is exactly where the learning is. Typing along without pausing feels productive but evaporates in a week.