Share This Infographic: 10 Truths about Deep Learning
Carlos E. Perez

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.

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