Understanding deep learning in 5 minutes

Most deep learning techniques are extensions or adaptions of ANN's, called deep nets. Different configurations of deep nets are suitable for different machine learning tasks: Restricted Boltzman Machines (RBM's) (Smolensky 1986; Hinton & Salakhutdinov, 2006) and Autoencoders (Vincent, Larochelle, Bengio, & Manzagol,2008) are the main deep learning techniques for finding patterns in unlabeled data. This includes tasks such as feature extraction, pattern recognition and other unsupervised learning settings.