title: ÐÐ¾Ð´ÐµÐ»Ñ Ð¼Ð°ÑÐ¸Ð½Ð½Ð¾Ð³Ð¾ Ð¾Ð±ÑÑÐµÐ½Ð¸Ñ Ð´Ð»Ñ ÐºÐ»Ð°ÑÑÐ¸ÑÐ¸ÐºÐ°ÑÐ¸Ð¸ ÑÐµÐºÑÑÐ¾Ð²ÑÑ Ð´Ð°Ð½Ð½ÑÑ Ð½Ð° Ð½ÐµÑÐºÐ¾Ð»ÑÐºÐ¸Ñ ÑÐ·ÑÐºÐ°Ñ
title: Ð²ÑÐ¿ÑÑÐºÐ½Ð°Ñ ÐºÐ²Ð°Ð»Ð¸ÑÐ¸ÐºÐ°ÑÐ¸Ð¾Ð½Ð½Ð°Ñ ÑÐ°Ð±Ð¾ÑÐ° Ð±Ð°ÐºÐ°Ð»Ð°Ð²ÑÐ°
titleType: Subtitle
title: Machine learning model for classification of text data in multiple languages
Creators: name: ÐÐ¾Ð»Ð¾Ð²Ð¸Ð½, ÐÐ¸ÑÐ¸Ð»Ð»
Publisher: name: Ð¡Ð°Ð½ÐºÑ-ÐÐµÑÐµÑÐ±ÑÑÐ³ÑÐºÐ¸Ð¹ Ð¿Ð¾Ð»Ð¸ÑÐµÑÐ½Ð¸ÑÐµÑÐºÐ¸Ð¹ ÑÐ½Ð¸Ð²ÐµÑÑÐ¸ÑÐµÑ ÐÐµÑÑÐ° ÐÐµÐ»Ð¸ÐºÐ¾Ð³Ð¾
Year: 2023
Subjects: Ð¼Ð°ÑÐ¸Ð½Ð½Ð¾Ðµ Ð¾Ð±ÑÑÐµÐ½Ð¸Ðµ
ÐºÐ»Ð°ÑÑÐ¸ÑÐ¸ÐºÐ°ÑÐ¸Ñ ÑÐµÐºÑÑÐ°
Ð¾Ð±ÑÐ°Ð±Ð¾ÑÐºÐ° ÐµÑÑÐµÑÑÐ²ÐµÐ½Ð½Ð¾Ð³Ð¾ ÑÐ·ÑÐºÐ°
ÑÐ·ÑÐºÐ¾Ð²Ð°Ñ Ð¼Ð¾Ð´ÐµÐ»Ñ
NLP
python
pytorch
machine learning
text classification
natural language processing
language model
PyTorch

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description: In the era of globalization and rapid development of information technologies, there is a growing demand for effective tools to process and analyze textual data in multiple languages. Despite significant progress in natural language processing, building a model capable of classifying texts in multiple languages remains a challenging task. However, the application of machine learning methods opens up new possibilities in this field. This paper presents machine learning models developed for text classification in multiple languages. They are based on state-of-the-art NLP algorithms and classification tools implemented using Python, PyTorch, FastText, and Scikit-learn. These models provide an efficient tool for text classification that can be applied in various domains, such as machine translation, sentiment analysis, and automatic document classification. Based on the analysis, assumptions were made about which model is most efficient considering the available production resources. Some models may be optimal for limited memory conditions or high response speed, while others may provide higher classification accuracy but require larger computational resources.