Abstract
The idea of Neural Network (NN) derived from brain activities which consists of neurons connected with thousands of their neighbors forming a very complex local network. As a discipline of artificial intelligence, neural network attempts to bring the computers closer to brain capability by simulating certain aspects of brain information system so that the NN has the ability to learn and generalize with higher processing speed. As an extension to NN, Deep Learning (DL) can handle high dimensional data with between leaning capability as feature extraction process became automatic. The aim of this paper is to present a review about NN and DL showing a detailed explanation of different architectures and algorithms.
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