I read somewhere that learning ML/AI isn't the hard part. It is having enough data science background to be able to tell tell what problems fit ML. ML isn't the hard part, finding a problem ML can approximate is.
Maybe that is too simplistic but I can't help after my 1 semester ML course think that most of the ML problems people are solving aren't really suited at all. Like SWE see this cool hammer and now everything is a nail. Maybe I should read up on startups using it successfully for anything but I haven't seen many of those on the frontpage.
Maybe that is too simplistic but I can't help after my 1 semester ML course think that most of the ML problems people are solving aren't really suited at all. Like SWE see this cool hammer and now everything is a nail. Maybe I should read up on startups using it successfully for anything but I haven't seen many of those on the frontpage.