You are right! LLMs accept the formulas and may explain them...
It will be more difficult to tell when they are wrong, though - when you cannot verify directly. But it will be a device for people to get acquainted with the math.
Be that as it may, this isn't what I'd call a "tutorial," in the sense that you'd better already have a strong command of the subject matter or you won't get much out of it.
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[ 3.4 ms ] story [ 42.0 ms ] threadEdit to add: I'm mostly interested in this aspect:
"The target audience of this tutorial includes [those] who are interested in [...] applying these models to solve other problems."
https://www.youtube.com/playlist?list=PLAqhIrjkxbuWI23v9cThs...
He is building new learning materials under his new company "Eureka Labs":
https://eurekalabs.ai
Sebastian Raschka's book "Build a Large Language Model (From Scratch) just released:
https://www.manning.com/books/build-a-large-language-model-f...
All of these resources are excellent.
https://www.youtube.com/watch?v=wjZofJX0v4M
I find the explanation in this article very intuitive.
It will be more difficult to tell when they are wrong, though - when you cannot verify directly. But it will be a device for people to get acquainted with the math.
https://huggingface.co/learn/diffusion-course/en/unit0/1
Trying to build a protein diffusion model from scratch right now.
The math explainer is quite helpful