Share This Infographic: 10 Truths about Deep Learning

Carlos E. Perez

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Unfortunately, this infographic, beside the obvious grammatical and syntax errors, is deeply flawed because it only sort of explains what Deep Learning is not. It’s kind of like describing a chair in terms of the set of all non-chairs. Or, to put it more succinctly, what does an orange taste like? Since that space isn’t defined, there is a problem. Perhaps some version of fuzzy logic or linear mixture modeling (LMM) would help constrain the solution space. Actually, since most of the known universe is non-linear, non-linear mixture modeling (NLMM) would be more appropriate. Of course, this assumes that you can create a set of end members which cannot be defined in this instance. Of course, one could fall back on Consensus Theory, too.