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R Deep Learning Projects by Pablo Maldonado, Yuxi Liu

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What makes deep learning special?

Deep learning employs a stack of multiple hidden layers of non-linear processing units. The input of a hidden layer is the output of its previous layer. This can be easily observed from the examples of a shallow neural network and a deep neural network shown previously.

Features are extracted from each hidden layer. Features from different layers represent abstracts or patterns of different levels. Hence, higher-level features are derived from lower-level features, which are extracted from previous layers. All these together form a hierarchical representation learned from the data.

Take the cats and dogs image classification as an example, in traditional machine learning solutions, the classification step ...

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