As someone studying ML at Berkeley right now: I’m noticing that people are increasingly trying to market ML as something that could be more mainstream (i.e., see Google autoML and andrew ng’s new books / startups), and an emphasis on tuning the models over fully understanding the underlying model. Do you think things like it that try and shorten the learning process in favor of technical knowledge, are sufficient for business use cases (non research) over having a graduate level understanding of the models?
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As someone studying ML at Berkeley right now: I’m noticing that people are increasingly trying to market ML as something that could be more mainstream (i.e., see Google autoML and andrew ng’s new books / startups), and an emphasis on tuning the models over fully understanding the underlying model. Do you think things like it that try and shorten the learning process in favor of technical knowledge, are sufficient for business use cases (non research) over having a graduate level understanding of the models?
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