+1 to that. It is like the ML people went out of their way to co-opt existing statistical terminology with a slightly different spin to completely muddle the waters.
At my department, instructors were well aware of statistics. That was a prerequisite course on the AI path. Some early day software (WEKA) used statistic nomenclature extensively.
The best part of DNNs I think is the brute force backprop over essentially randomized feature generation (convolutions)… Statisticians would never do that.
+1 to that. It is like the ML people went out of their way to co-opt existing statistical terminology with a slightly different spin to completely muddle the waters.
It's just because they did not study statistics, so they were unaware of it.
https://www.andrew.cmu.edu/user/mhydari/statistics.ML.dictio...
At my department, instructors were well aware of statistics. That was a prerequisite course on the AI path. Some early day software (WEKA) used statistic nomenclature extensively.
The best part of DNNs I think is the brute force backprop over essentially randomized feature generation (convolutions)… Statisticians would never do that.