Deep Learning

Neural network fundamentals: training dynamics, normalization, and optimization.

2 articles / papers

Core deep learning ideas that show up across architectures and domains.

Covered in

Quick notes on how model performance scales with parameters, data, and compute.

Review of the seminal transformer paper that introduced self-attention as the sole mechanism for sequence transduction.