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COLLOBATION FORMS OF LEARNING
Ibragimov, D.R., Aitova, L.R., Timerbulatov, M.V. (2023)
learning. Distance form of education is the receipt of educational services without visiting an educational
DISADVANTAGES AND ADVANTAGES OF DISTANCE LEARNING
Fazlutdinova, L.R., Gainullin, R.A., Yulmukhametov, A.A. (2023)
The article discusses the nuances of distance learning at the university, highlights the advantages
THE ADULT LEARNING THEORY PRINCIPLES
Tselousova, O.S., Ovsyannikova, L.B. (2023)
the andragogy approach of today’s methodology. There are six main assumptions in adult learning theory. They are
DIGITAL TOOLS IN LEARNING STUDENTS OF PEDIATRIC FACULTY
Yakovleva, L.V., Kuchina, E.S., Tikhonova, R.Z. (2023)
DIGITAL TOOLS IN LEARNING STUDENTS OF PEDIATRIC FACULTY
Predicting Threat Degree for Onset of Type 2 Diabetes Mellitus Based on Machine Learning Methods
Shakhmametova, G., Vakkazov, N., Klimets, S. (2023)
This article discusses the use of machine learning methods to predict the degree of threat
Machine Learning Algorithms for the Analysis of Age-Related Macular Degeneration Based on Optical Coherence Tomography: a Systematic Review
Lopukhova, Ekaterina A., Ibragimova, Rada R., Idrisova, Gulnaz M., Lakman, Irina A., Mukhamadeev, Timur R., Grakhova, Elizaveta P., Bilyalov, Azat R., Kutluyarov, Ruslan V. (2023)
is expressed in the application of various machine learning algorithms, metrics for evaluating
IT-TECHNOLOGIES AS A WAY TO TEACH PHYSICAL EDUCATION AND SPORT TO FOREIGN STUDENTS UNDER PANDEMIC CONDITIONS AT BSMU
Zakiev, A.M., Khadiyatov, R.Z. (2023)
In the article methods of distance learning organization with application of IT
Machine Learning Methods and Models for Recognizing Lung Inhomogeneity from Computed Tomography Scans
Shakhmametova, G. R., Stepanova, E. S., Akhmetshin, A. A., Zulkarneev, R. Kh. (2023)
-platform. For machine learning algorithms, PyTorch 1.9.0 packages were used. An analysis of the effectiveness
Использование методов машинного обучения в диагностике и прогнозировании клинических особенностей шизофрении: нарративный обзор литературы
Machine Learning Techniques in Diagnostics and Prediction of the Clinical Features of Schizophrenia: A Narrative Review
Gashkarimov, Vadim Rimovich, Sultanova, Renata Ildarovna, Efremov, Ilya Segeevich, Asadullin, Azat (2023)
and patient’s quality of life. In this context, machine learning techniques open up new opportunities for a
APPLICATION OF DIGITAL TECHNOLOGIES WHEN TEACHING CHEMISTRY TO FOREIGN STUDENTS
Gabbasova, I.M., Shumadalova, A.V., Shamsutdinova, S.R., Korolev, V.V., Meshcheryakova, S.A. (2023)
online learning

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