Рақамли технологияларнинг назарий ва амалий масалалари 9-tom 3-san (2026) · 166-174-betler
A neural network model for determining the educational pathways of school graduates
Маллаев, О., Алиев, Ж., Фозилов, О.
Annotaciya
This paper presents a model based on machine learning and artificial neural networks for predicting the educational pathways of school graduates. Within the study, a dataset comprising 20 features was constructed, reflecting students’ academic performance, subject interests, soft skills levels, and psychological factors. Based on a dataset containing 2,000 records, five machine learning algorithms -Logistic Regression, Random Forest, Support Vector Machine, K-Nearest Neighbors, and Neural Networks - were comparatively analyzed. Experimental results demonstrate that the neural network model exhibits high efficiency in identifying complex nonlinear relationships. The models were evaluated using standard performance metrics, including Accuracy, Precision, Recall, and F1-score. The findings indicate that artificial intelligence-based systems can play a significant role in automating the process of determining students’ career pathways and improving career guidance systems within educational institutions.
машинное обучениенейронная сетьобразовательная аналитикапрофориентацияискусственный интеллектmachine learningneural networklearning analyticscareer guidanceartificial intelligence
Metadata derekkózi: jurnal OAI-PMH arxivi · Sindex tolıq mátindi saqlamaydı, derekkózge silteme beredi.