Lecture 4: Convolutional Neural Networks, Autoencoders, Principal Component Analysis Contents: A bit more on image recognition, convolutional neural networks as an efficient way to process images and other data with translational invariance, (kernels, channels, and so on), autoencoders for unsupervised learning and information compression, principal component analysis as a simple linear way to extract the main (linear) features of data sets Lecture series by Florian Marquardt: Introduction to deep learnin
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