a) perhaps &quot;feature engineering&quot; was not the right 2-gram. I was looking for the (cultural) difference in approaches. Logic programming starts with background knowledge, predicate logic, and hand-written rules on what is valid and what isn&#x27;t. Deep learning is trying to learn this bottom-up. When DL finds a rule or fact it did so from data, not by using any pre-defined rules or facts.<p>b) if we apply hierarchical clustering, it would probably be a subset.<p>Anyway, this was more or less tongue-in-cheek. And yes, you could go on and on. I should have added &quot;The Logicians&quot;, &quot;The Game Theorists&quot; and the NLP&#x27;ers solving object detection problems with visual bag-of-words. Also forgot to take a jab at business intelligence&#x2F;operations research.<p>As for being wedded to a favorite technique, I think that is largely a problem for beginners (and PhD. students with a supervisor who can only think from within a certain framework). I myself may try SVM, but I rank it pretty low as an alternative.