This is decent for what it is. Some of the problems are pretty open ended which has pros and cons, but that is very different from leetcode, which has very specific data and test cases.

For example, implement linear regression but the example solution uses a random number generator without a fixed seed. It’s fine, reproducibility isn’t the point, but leetcode problems are more structured.

In leetcode they usually don’t tell you exactly what data structure you must use, only that it must pass certain test cases. By analogy this might not tell you which architecture to use but require that it passes certain eval metrics.

Cool idea, will try. Since it seems mostly llm generated you could publish the process and prompts for transparency.

> Avoid using GPT. Try to solve these problems on your own. The goal is to learn and understand PyTorch concepts deeply.

I mean...this entire project appears to be mostly GPT-generated?

What are people's other "go try to build this thing, perfectly aligned to your noob-level" ways of learning lower-level ML Tools (PyTorch, CUDA etc.)?

It helps me a lot!!

Is it just me or does anyone else find the red squiggly lines under Pytorch and Leet hilarious in the heading picture?

super helpful, thanks for sharing!

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