The neural network imitates not only the activity, but also the structure of the human nervous system. Such a network consists of a great number of individual processing elements that can be called “ neurons “. In most cases each “neuron” refers to a definite layer of the network. Input data is processed consistently on all layers of the network. The parameters of each “neuron” can vary depending on the results obtained in the previous input datasets, thus altering the order of work of the whole system.

The Neurosphere’s area manager of “ Business use of Neural Networks “ notes that neural networks can solve the same tasks as other machine learning algorithms, the only difference being the approach to learning.

All tasks that neural networks can perform are somehow linked to training. The main applications of neural networks include forecasting, decision making, pattern recognition, optimisation, data analysis.