For those curious about writing a "gradient descent with respect to some loss function" starting from an empty .py file (and a numpy import, sure), can't recommend enough Harrison "sentdex" Kinsley's videos/book Neural Networks from Scratch in Python [1].
The beginning of Andrew Ng’s machine learning course on coursera does that too, it touches on the math a bit and explains how to imagine gradient descent in 3d space
Didn’t do the full course, but after the first few chapters I was able to write a very basic implementation in raw python (emphasizing here on “very basic”)
Didn’t do the full course, but after the first few chapters I was able to write a very basic implementation in raw python (emphasizing here on “very basic”)