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The aim of this paper is to present some of the main aspects of deep learning, that set it apart from traditional machine learning algorithms and that make it possible for it to perform much better in some cases.  The rest of the paper is structured as follows: section~\ref{sec:unsupervised} presents the two main unsupervised deep learning approaches, while  section~\ref{sec:supervised} presents some of the improvements used in the supervised setting, while section~\ref{sec:application} presents the results obtained using deep learning on several data sets. setting.