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ML is a very applied subject. There is entirely too little theory people need to know. In fact the most impressive vision/nlp architectures are indeed uninterpr

ML is a very applied subject. There is entirely too little theory people need to know. In fact the most impressive vision/nlp architectures are indeed uninterpretable alchemy. It would make very little difference to study it at a university. Unless of course you 're going for probability theory.

unishark 7y ago
Are you defining "need to know" as in the state of the art methods of today? Problem is the next stage after mature technology is commodity. We'll be getting daily spam from India offering to fulfill all our "A.I. design" needs just as with web design. If all you have to do is follow a blog post or video on how to use a prepackaged framework to get a job done, than everyone else can do it too.
- rckoepke 7y ago
  And honestly those commodity AI networks from India will probably solve 90% of corporate needs, when properly pipelined.
- buboard 7y ago
  i thought we are already at this stage? You can find plenty of tutorials on how to e.g. use BERT and there's plenty of people who will do that for you