Great answer. Imbuing a deep learning model with well thought out inductive biases is one of the strongest ways of guiding your model to interpret the data the way you want it to. Otherwise it’s kind of shooting in the dark and hoping to get lucky.
I can’t stand it when people lazily personify ML models, but it’s akin to giving someone with no experience some wood and then pointing to a shed and saying “make one of those from this”. Instead you’d expect them to be much more successful if you also give them a saw, a drill, some screws etc.
I can’t stand it when people lazily personify ML models, but it’s akin to giving someone with no experience some wood and then pointing to a shed and saying “make one of those from this”. Instead you’d expect them to be much more successful if you also give them a saw, a drill, some screws etc.