Abstract
The article describes the implementation of the weather classification service in the territory and the use of a deep neural network to solve the classification problem. It is noted that deep neural networks have a high efficiency index with a fairly complete set of training data. The deep neural network model is based on data that was received from the ERA-5 satellite, the data consists of 11 parameters such as latitude, longitude, time, wind components, temperature, pressure and others. The analysis of the existing methods of weather classification is also carried out. The article describes the application of a deep neural network in the context of weather forecasting, and also includes consideration of the importance of having a sufficient amount of training data for the successful application of machine learning methods
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