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Covers advanced counting techniques, including linear recurrence relations and generating functions, with examples from the Fibonacci sequence and differences between dice and poker cards.
Covers the foundational concepts of deep learning and the Transformer architecture, focusing on neural networks, attention mechanisms, and their applications in sequence modeling tasks.
