Good points. How about you the following though: driven by all the hype surrounding deep learning and AI, consultants are currently jumping on this new thing they can sell to management without understanding much of the intricacies behind it, so even after facing many disillusions just a few years ago when the talk was all about big data, companies are now jumping towards investing in products promising some of that sweet deep learning magic.
That's fine, but the thing is they once again plan to apply it on their badly maintained data warehouses (now often somewhere in their dusty hdfs stack) to build traditional predictive models. Customer churn, next best offer, propensity modeling, that sort of thing.
I try to keep telling them that with structured data sets, and simple classification problems, a random forest or God forbid, a logistic regression model, would do just as well given that you spend some solid time in feature cleaning and preprocessing. Am I wrong in this setting? Perhaps I should also jump on the deep learning bandwagon and start selling 10 layer binary Classification networks :).
Not disagreeing with you, but I do fear that many traditional industries will be jumping on board pretty soon without any of the actual use cases to warrant deep learning.
That's fine, but the thing is they once again plan to apply it on their badly maintained data warehouses (now often somewhere in their dusty hdfs stack) to build traditional predictive models. Customer churn, next best offer, propensity modeling, that sort of thing.
I try to keep telling them that with structured data sets, and simple classification problems, a random forest or God forbid, a logistic regression model, would do just as well given that you spend some solid time in feature cleaning and preprocessing. Am I wrong in this setting? Perhaps I should also jump on the deep learning bandwagon and start selling 10 layer binary Classification networks :).
Not disagreeing with you, but I do fear that many traditional industries will be jumping on board pretty soon without any of the actual use cases to warrant deep learning.