In recent years, we have seen a huge interest in neural networks, which are successfully used in various areas—business, medicine, technology, geology, physics, and so on. Neural networks have come into practice wherever it is necessary to solve problems of forecasting, classification, or control. This approach is attractive from an intuitive point of view because it is based on a simplified biological model of the human nervous system. It arose from research in the field of artificial intelligence, namely, from attempts to reproduce the ability of biological nervous systems to learn and correct mistakes by modeling the low-level structure of the brain. Neural networks are compelling modeling methods that allow us to reproduce extremely complex dependencies because they are non-linear. Neural networks also cope better with the curse...
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