A number of useful points are embedded here. Useful to know these objections, since they will be brought up by thoughtful management. These are high level observations. I am not sure I would call all of these 'myths'. They all have elements of caution and truth to them, but the author also suggests under what contexts they might be true or not. In the real world you are always under some assumptions for any kind of useful modeling, so its useful to know what they are. Machine Learning Myths.
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