Deep learning

Deep learning (also known as deep structured learning or hierarchical learning) is part of a broader family of machine learning methods based on learning data representations, as opposed to task-specific algorithms. Learning can be supervised, partially supervised or unsupervised

Deep learning is a class of machine learning algorithms that

·         use a cascade of many layers of nonlinear processing units for feature extraction and transformation. Each successive layer uses the output from the previous layer as input. The algorithms may be supervised or unsupervised and applications include pattern analysis (unsupervised) and classification (supervised).

·         are based on the (unsupervised) learning of multiple levels of features or representations of the data. Higher level features are derived from lower level features to form a hierarchical representation.

·         are part of the broader machine learning field of learning representations of data.

·         learn multiple levels of representations that correspond to different levels of abstraction; the levels form a hierarchy of concepts.

·         use some form of gradient descent for training

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