It'd be a lot more accurate—not to say more honest—to say the author _estimated_ the number of all the yurts in Mongolia using machine learning. ML algorithms are stochastic; their outputs are whatever the algorithm deems the most probable of the options generated from the given inputs. They barely give a thought to all the ways their count could be wrong—no error analysis, no confidence intervals. There's a meaningless prediction score of 40%, and they blithely add "a hundred or so" to the count.

This is anti-information. People reading this uncritically will come away with completely wrong ideas about the number of yurts in Mongolia, about machine learning algorithms, about data science in general.