garbage in = garbage out class mistakes need stats competence to untangle. Self-proclaimed ML practitioners seem to lack this.
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applied stats is a fundamental skill many so-called data scientists seem weak on (myself included).
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Statistics is just lies and magic. As is machine learning. It's a match made in heaven ;)
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indeed! But srsly.. seems like the same ppl who can barely put error bars on perf benchmarks are stumbling
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through self-assessing the validity of their algorithms
End of conversation
New conversation -
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@Grifter801@desmondholden I thought you guys used big data machine learning clouds to analyze CFPs?Thanks. Twitter will use this to make your timeline better. UndoUndo
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@Grifter801 1) Get big data 2) Machine Language it 3) ...? 4) VALUE!Thanks. Twitter will use this to make your timeline better. UndoUndo
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@desmondholden I volunteer to shot down bullshit in that area.Thanks. Twitter will use this to make your timeline better. UndoUndo
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