![]() ![]() (Neural networks can also extract features that are fed to other algorithms for clustering and classification so you can think of deep neural networks as components of larger machine-learning applications involving algorithms for reinforcement learning, classification and regression.) They help to group unlabeled data according to similarities among the example inputs, and they classify data when they have a labeled dataset to train on. You can think of them as a clustering and classification layer on top of the data you store and manage. ![]() Neural networks help us cluster and classify. The patterns they recognize are numerical, contained in vectors, into which all real-world data, be it images, sound, text or time series, must be translated. They interpret sensory data through a kind of machine perception, labeling or clustering raw input. Neural networks are a set of algorithms, modeled loosely after the human brain, that are designed to recognize patterns. ![]()
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