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I honestly didn't realise that it had any definition - I see now that calling it a 'fad' is unfair. However, the boundary between deep learning and (representational) machine learning still seems murky.

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Considering the very significant accuracy gains deep learning has achieved over previous approaches (and across a number of fields), it's certainly not a simple fad. Having worked in computer vision for a good 8+ years, deep learning is basically amazing.

Deep learning is a form of representation/feature learning.

Machine learning proper encompasses a swath of applied statistical techniques, of which deep learning is only one. Machine learning could refer to linear regression, SVM, hidden markov models, dimensionality reduction, neural nets, or any number of other loosely related methods. Intro ML classes often don't even get to deep learning because theres so much more fundamental stuff to cover.

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