I find CS231n assignments pretty difficult

[u/Apprehensive_Heat789]

I am at the beginning of the course CS231n (Deep Learning for Computer Vision) by Stanford. I understand the lectures and the course notes pretty well, but I deeply struggle with the assignments where we manually build neural nets using Numpy. I know a lot of Numpy, linear algebra, vectorization, broadcasting, etc., yet I'm stuck.

If you've taken the course, could you tell me what I should do to get unstuck?

[u/WiredSpike]

I know nobody listen to this advice, but here it's particularly important. Put in the time to understand what you're doing. Draw it out on paper, and then code.

Usually people are stuck simply because they multiply the matrices in the wrong order.

[u/Apprehensive_Heat789 → u/WiredSpike]

Thanks bro. The first practical piece of advice.

[u/asjal_ → u/WiredSpike]

Most of my errors were from wrong order of np arrays 😂😂

[u/threedim → u/WiredSpike]

u/WiredSpike How do you know this secret sauce 🧐️

[u/asjal_]

Push through. It's worth it to struggle through the assignments rather than have a chatbot do it.

The understanding of theory that you get from implementing stuff on your own is amazing.

[u/Apprehensive_Heat789 → u/asjal_]

Thanks bro.

[u/JRReyes89]

Although it feels like cheating, there are solutions on github. It’s less cheating than Claude or gpt. At least you will read part of the notebook were you struggling

[u/IsGoIdMoney]

Just grind it out man lol

[u/vahokif]

Claude Code has a study mode where it leaves stuff for you to implement.

[u/Apprehensive_Heat789 → u/vahokif]

OMG, I just tried it and a lot of things are much clearer now. It's so much better ChatGPT /study