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Knowledge-Distillation

Mentor: Prof. R.M. Hegde, Department of Electrical Engineering, IITK

– Learned deep learning models using PyTorch with both fully connected and convolutional architectures.

– Evaluated student-teacher model performance in terms of accuracy and parameter efficiency.

– Implemented and compared three major KD strategies — response-based, feature-based, and relation-based distillation — on the FashionMNIST dataset.

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