Deep Neural Network
A Deep Neural Network (DNN) is a type of Artificial Neural Network (ANN) that consists of multiple hidden layers between the input and output layers. Each hidden layer is composed of a set of neurons that perform a nonlinear transformation on the input data. The number of hidden layers and the number of neurons in each layer can vary depending on the complexity of the problem being solved. DNNs are trained using a process called backpropagation, which adjusts the weights of the connections between neurons to minimize the difference between the predicted output and the actual output. DNNs have been successfully applied to a wide range of tasks, including image and speech recognition, natural language processing, and game playing.
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