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I am reading the programme outline of this two-year MSc in Data Science and I found that it has no deep learning content (as in many other european ones). I am no expert but as far as I've seen I think that DL is going to be a heavy weight of ML algorithms for a long time.

Do you think it is a bad idea to take a strong focus on classical models (e.g. bayesian) instead of teaching DL in a Data Science/ML MSc?

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  • $\begingroup$ What do you think the basics of DL are? CLASSICAL MODELS $\endgroup$ – Dawny33 Aug 12 '16 at 9:51
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No, it's not problematic. Most data scientists do not need or use deep learning. Deep learning is very popular right now, but that does not mean it's widely used. Deep learning can lead to substantial overfitting on small to medium datasets (I'm arbitrarily going to say that means less than 2 GB), which are the sizes that most people have. Deep learning is primarily used for object recognition in images, or text/speech models. If you're not doing either of these two things, you probably don't need to use DL.

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  • $\begingroup$ The combination of reinforcement learning and DL also becomes also popular in game AI (go, Mario, flappy bird) $\endgroup$ – Pieter Aug 12 '16 at 22:28

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