Building Attention from Scratch
Implement the attention mechanism that powers transformers, from matrix operations to multi-head attention, with clear PyTorch code.
Neural networks, transformers, and LLMs explained from first principles—with working implementations you can run and modify.
Explore ArticlesDeep dives into AI concepts with production-ready code examples
Implement the attention mechanism that powers transformers, from matrix operations to multi-head attention, with clear PyTorch code.
Build a miniature GPT model that actually generates coherent text. Covers tokenization, positional encoding, and training loops.
Why do LLMs represent words as vectors? Learn the intuition behind embeddings and build your own word2vec implementation.