Deep learning: Architectures, algorithms, applications
Roland Memisevic · 2015
This article consists of a collection of slides from the author's conference presentation. Some of the topics covered include: Machine learning 101: Neural nets, backprop, RNNs; Applications; Structured prediction; Unsupervised learning; "Neural Programs"; Architecture exploration; Towards hardware-friendlier DL; and Software.