Course Overview
Course objectives, mathematical foundations, and learning outcomes.
Course Page
Deep Learning
From neural-network fundamentals to convolutional, recurrent, attention-based, and transformer architectures.
Weekly Notes
Lectures on neural networks, CNNs, RNNs, attention, and transformers.
Code and Colab
PyTorch and Python notebooks, training examples, and model implementations.
Assignments and Exams
Programming assignments, sample questions, and assessment materials.