Explores random binning in advanced information theory, focusing on assigning labels based on typicality and achieving negligible error rates in source coding.
Covers the foundational concepts of deep learning and the Transformer architecture, focusing on neural networks, attention mechanisms, and their applications in sequence modeling tasks.
