Sun’iy intelekt, axborot xavfsizligi texnikasi va texnologiyalari
Международная научно-техническая конференция «Практическое применение технических и
цифровых технологий и их инновационных решений», ТАТУФФ, Фергана, 4 мая 2023 г.
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its performance over time. This may involve updating the model with new data
or retraining the model if performance degrades over time.
Throughout this process, it is important to continually evaluate and refine
the system, using feedback from students
and teachers to improve its
performance and effectiveness. By leveraging the power of artificial neural
networks, this methodology has the potential to transform the way we teach and
learn, making education more personalized, efficient, and effective.[2,3]
Algorithms that can be used to train Artificial
Neural Network-based
Intelligent Learning Systems include stochastic gradient descent, momentum-
based gradient descent, and adaptive learning rate algorithms such as Adam and
RMSprop. The choice of algorithm depends on the specific problem and data set
being used.
In
conclusion, an Artificial Neural Network-based Intelligent Learning
System is a powerful tool that can be used to enhance
learning and improve
educational outcomes. By leveraging the principles of machine learning and
artificial
intelligence, this technology can provide personalized feedback and
recommendations to students and teachers, and adapt to changing learning needs
and preferences.
