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To give a brief one-line description of machine learning: It is basically a function approximation given sample and hypothesis class. But this question is already tackled by statisticians (parameter as well as non-parameter). So is it a old wine in a new bottle?

Manish Kumar Singh
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    You may want to read Leo Breiman’s paper “Statistical Modeling: The Two Cultures”. It gets at the difference in outlooks and approaches between the ML and classic stats paradigms. – Arya McCarthy Nov 29 '21 at 12:40
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    @Dave Maybe you could help us understand what the question is? With the typos, the informal language, and structural problems with the English, I just can't make sense of it. – whuber Nov 29 '21 at 14:22
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    Perhaps you meant "function approximator" rather than "function appropriator"? Please clarify. – Galen Nov 29 '21 at 14:38
  • Is "hypothesis lass" intented to be "hypothesis and loss"? – Galen Nov 29 '21 at 14:39
  • @Galen it was probably meant to be "hypothesis class". – Arya McCarthy Nov 29 '21 at 15:17
  • @AryaMcCarthy That would make more sense. Hopefully the OP clarifies. – Galen Nov 29 '21 at 15:44

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