Karabakh University Courses
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[DAM 305] Deep Learning
Instruction Language
Azerbaijani
Course Description
This course explores advanced neural network architectures designed to model complex patterns in large datasets. The curriculum focuses on deep feedforward networks, convolutional neural networks (CNNs) for image recognition, and recurrent neural networks (RNNs) for sequential data. Students investigate backpropagation algorithms, optimization techniques like Adam, and the role of dropout layers in preventing overfitting. The course emphasizes the use of frameworks such as TensorFlow or PyTorch. By the end of the semester, students will be capable of designing and training deep models for speech recognition, computer vision, and generative AI, providing cutting-edge expertise for research and industry.
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