Neural networks were originally introduced in 1943 by McCulloch and Pitts as an approach to develop learning algorithms by mimicking the human brain. The major goal at that time was to introduce a sound theory of artificial intelligence. However, the limited amount of data and the lack of high performance computers made the training of deep neural networks, i.e., networks with many layers, infeasible.

Nowadays, massive amounts of training data are available, complemented by a tremendously increased computing power, allowing us for the first time to apply deep learning algorithms in practice. It is for this reason that deep neural networks have recently seen an impressive comeback. Spectacular applications of deep learning are AlphaGo, which for the first time enabled a computer to beat the

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