The work describes the approaches and technologies applied in building the digital educational environment for training students of engineering courses in MIEM HSE. Such an environment intended to cover all aspects of the educational process for engineers, considering modern tendentiousness of higher education: particularly, academic and project parts, online and offline components of the educational process.

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Sentiment analysis of different language texts is one of the very popular machine learning tasks. The complexity of its solution depends both on the characteristics of a particular language, and on the length of the evaluated texts. In our work, we consider the task of creating a sentiment analysis software tool for Russian posts and comments from the most popular social networks without any domain restriction. The features of constructing both the algorithmic and the software parts of the problem are described, some quality and performance metrics of the suggested neural network system are presented.

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