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Deep learning is a hot research topic these days. Neural networks are the workhorses of deep learning. In this research the basics of neural networks were studied. ANNs may be defined as structures comprised of densely interconnected adaptive simple processing elements (called artificial neurons or nodes) that are capable of performing massively parallel computations for data processing and knowledge representation. Definition of artificial neural network was mentioned , design of neural network was discussed, learning of neural network was studied, the most popular types of neural net- worksuch as Hopfield networks, Adaptive resonance theory (ART) networks, Kohonen networks, Backpropagation networks , Recurrent networks, Counter propagation networks and Radial basis function (RBF) networks were discussed.Also General issues in ANN development were studied.