There are many sources of news.
Sometimes you want to read news by a specific category (for example, just Sports and|or Business).
Some news resources don't have news categories or their grading is rather arbitrary.
Our client came up with the idea of a news aggregator that they would like to see in their app.
The concept of the aggregator is a model that categorizes the news text from several sources into 10 topics:
Classification models were trained for two languages: Russian and Kazakh.
The news language is detected by a model based on a perceptron, which was trained on the collected data of Russian and Kazakh.
The categorizer model is based on the LSTM (long short-term memory) neural network. In practice, the model has shown a good quality of news categorization (validation accuracy more than 0.93), provided it is multi-label and multi-category.