lab-grad

Very very cool to see!!! So yours is SO MUCH MORE fleshed out than mine, but I have a similar (again very fledgling) one going here that uses Typescript: https://github.com/Marviel/lab-grad I think there are some really neat opportunities to increase the approachability of ML algorithms when you take advantage of the Typescript templating system to explicitly ensure you're not accidentally composing tensors of incorrect shapes. Unfortunately, my above lib above doesn't yet handle tensors, it's still at the level of individual neurons. Hopefully someday I can bring it further along, use WASM or WebGPU, etc. :)

I have taken several masters-level courses in Machine Learning -- and even with those credentials, I cannot recommend enough Andrej's youtube series, "Neural Networks: Zero to Hero". There, he teaches you, from scratch, how to build everything from the underlying automated gradient calculation system in pytorch, all the way up to the slower version of this model - `MinGPT`. [1] https://www.youtube.com/playlist?list=PLAqhIrjkxbuWI23v9cThs... (edit: self-promo: I'm currently working on a Typescript follow-through of this same series of video lectures, if you want to follow along with stronger types for explanation: https://github.com/Marviel/lab-grad)