This article explores the integration of neural networks into the architectural design of educational institutions, emphasizing their potential to create adaptive and personalized learning spaces. The study highlights the role of artificial intelligence in transforming static environments into dynamic and responsive educational ecosystems. By analyzing current trends, theoretical frameworks, and practical examples, the research demonstrates that neural networks can enhance flexibility, ergonomics, and personalization of space usage. A conceptual model is proposed, in which machine learning systems continuously monitor, analyze, and adjust architectural and interior parameters to improve the quality of education.

neural networks, architectural design, educational institutions, adaptive learning spaces, personalization, artificial intelligence.

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