This repository collects and standardizes mathematical notation, typographic conventions, and symbol definitions used in the Deep Learning Book (by Goodfellow, Bengio & Courville). Its main goal is to provide a canonical reference for notation so that derivative works (papers, lectures, tutorials) can align notation consistently. The content includes LaTeX macros, notation tables (e.g. symbols for vectors, tensors, functions, loss, activation), and cross-references mapping symbols to their conceptual meaning. It also includes scripts or style files to facilitate inclusion in articles, slides, or papers that build on the DL book’s notation. Researchers and educators often use this repo when writing materials referencing the deep learning book, so their formulas align with the canonical style. Because notation consistency is crucial in ML education, this repo helps reduce confusion when multiple sources adopt conflicting symbols.
Features
- Canonical symbol tables and definitions from the Deep Learning Book
- LaTeX macros / style files to standardize notation in papers and slides
- Mapping from symbols to conceptual meaning
- Cross-references to chapters/sections of the book to show usage context
- Support for embedding notation in derivative works (presentations, tutorials)
- A community reference to harmonize notation across deep learning literature