Integration of neural networks into the educational process for solving practical problems in mathematics at the university

the article is devoted to the study of the introduction of neural networks into the educational process for solving practical problems in mathematics at the university. With the rapid development of technology and the increasing volume of data, neural networks are becoming an important tool for students, allowing them to apply theoretical knowledge in real-world scenarios. This not only facilitates faster learning of the educational material, but also allows for in-depth study of complex mathematical theories such as linear algebra, probabilistic methods and optimization. The use of neural networks in solving practical math problems significantly increases students' motivation and involvement in the learning process. Students working with neural networks have the opportunity to see how theoretical knowledge is applied in practice, making learning more interactive and productive. The article also discusses the implementation of neural networks in educational activities through project work. This approach involves considering a wide range of topics such as image classification, natural language processing, time series forecasting, and text generation. Project work allows students not only to study and consolidate theory, but also to implement it on real-world tasks, working both in groups and independently. This learning format promotes the development of teamwork and critical thinking skills, as well as helps students better understand how to apply mathematical concepts in various fields. Examples of successful applications of neural networks in solving mathematical problems illustrate how these technologies can significantly increase student motivation and engagement. This not only makes learning more interesting, but also prepares students for the real challenges they may face in their professional careers.

neural networks, mathematics, data analysis, programming, practical tasks in mathematics, modern technologies, the study of neural networks at the university, the educational process