I agree that the size of libraries is probably important. For many ML models, things like the under-the-hood optimizer are doing a lot of the “real work”, IMO, rather than the source code that uses the libraries, which is usually much terser.
I agree that the size of libraries is probably important. For many ML models, things like the under-the-hood optimizer are doing a lot of the “real work”, IMO, rather than the source code that uses the libraries, which is usually much terser.