Semi-related question: Why did the ML people choose Python and make it so intertwined with ML? It seems like a bad choice because it's slow and bad at integrating with hardware, the actual hardcore ML stuff gets offloaded to C, which creates a weird system with two languages and a weird build step to achieve one thing. If I knew nothing about the ecosystem of available libraries and was asked to pick a language to use for ML, Python would be fairly low down the list.
Is it just because it's easy, somebody picked it a while ago, made something influential, and now everybody uses it because everybody uses it?
Is it just because it's easy, somebody picked it a while ago, made something influential, and now everybody uses it because everybody uses it?