Learning Deep Learning the EASY way, with Keras
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Author of Learning Deep Learning here.
How to solve a practical problems requires much more well-rounded skills that mastering one machine learning algorithm or another (in fact, some problems don't require ML at all).
For a more general introduction to data science, see http://p.migdal.pl/2016/03/15/data-science-intro-for-math-phys-background.html. So yes: discussing things with clients, getting data, cleaning data, realising it is not enough, so asking client if they have more/different data, exploring it, seeing that some of it is rubbish, semi-manually cleaning it, creating a model, seeing it's ok, discovering that it fitted to some artefact, ... (and dozens, dozens of steps).