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In what sense?



their proliferation as half-assed projects that all accomplish the same thing, but differ in their all-too-similar implementation languages.

I don't mean this particular project, but generally, you can't be in the field without seeing ten frameworks a day.


With the primary difference being web frameworks are much better documented with real world examples because they are written by people in industry trying to make their real jobs easier, not university grad programs. The examples released by users never make it onto the search engines, if ever released (see below).

Most ML frameworks out there are stuck in academic-land and assume the users are experts - when the exact opposite is usually true - they actually attempt to use the most opaque language possible when describing usage.

ML is still a consulting gold mine because it's so difficult to wade past the jargon and bullshit to actually do something useful/profitable with these frameworks.




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