Аннотация
The fast progress of artificial intelligence (AI) technologies is changing fields like education and healthcare greatly. One promising area for AI is deaf education. A sector that supports education for people with hearing impairments. Traditionally, deaf education has used methods and tools to aid learning and communication, for those who are deaf or hard of hearing. Nevertheless the inclusion of AI in this area presents possibilities to boost educational results and enhance the well being of individuals, with hearing challenges. Programming of such projects such as sign language recognition improves communication accessibility. However, in addition to the technical aspects, it is important to consider the cultural and social contexts in which sign language is used. The concept of research work for sign language translation is learning and using Python: for Gesture Character Recognition analysis of computer vision and machine learning methods, as well as the development of Python software for image processing for recognition purposes. The development of algorithms based on approaches to deep learning and machine learning of gestures helped to create a system capable of recognizing and translating a language. The main four steps that the project includes: 1) using computer vision, the silhouette of the hand is determined; 2) a letter is indicated with a hand gesture in front of the camera; 3) the definition of the sign using machine learning; 4) the result is displayed on the screen. The developed system allows you to determine the letters to a high degree and display the result on the screen. These results show that machine learning and computer vision have advantages and relevance in society. Key words: sign language, python (programming language), computer vision, machine learning.