LLM Math Basics 2: Softmax and Probability Interpretation
A walkthrough of how softmax converts raw scores into probability-like values, with formulas, explanations, and examples.
A walkthrough of how softmax converts raw scores into probability-like values, with formulas, explanations, and examples.
A walkthrough of vectors and the dot product — with notation, explanations, and examples — covering what you need to know before reading LLM papers.
A Map of Content page for reading core LLM papers in order, starting from the Transformer.
Explains the role of Q, K, and V through the attention formula, a plain-language walkthrough, and a concrete example.
Why Residual, LayerNorm, and FFN are necessary in a Transformer block — explained with equations, commentary, and examples.