I&#x27;m going through the course right now, and the instructor is saying some strange things, clearly (to me) ignoring that what he&#x27;s saying is only true in very specific contexts.<p>For example, in the video I just watched he said &quot;the natural way to compute the distance between two vectors is using cross entropy.&quot; And then he goes on to describe some unnatural features of cross entropy. The truly &quot;natural&quot; way to compute distances between vectors is the Euclidean distance, or at least any measure that has the properties of a metric.<p>I can understand this is a crash course and there isn&#x27;t time to cover nuances, but I&#x27;d much rather the instructor say things like &quot;one common&#x2F;popular way to do X is...&quot;  rather than making blanket and misleading statements. Or else how can I trust his claims about deep learning?