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Deep learning: Architectures, algorithms, applications
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.
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