Deep convolutional neural networks have led to breakthrough results in numerous machine learning tasks such as the classification of images in huge data sets, like ImageNet ; they have provided the framework for unsupervised control-policy-learning in the mastering by computers of sample human tasks, like Atari games; and have led to the defeat of the world champion, in the complex and computationally intractable, game of Go, a decade before computer scientists thought it possible. All of these applications first perform feature extraction on large data sets and then feed the results into a trainable classifier based on deep convolutional neural networks. This paper presents an introduction to deep learning and the theory of convolutional neural networks large convolutional neural networks.
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