Comparing BM25 and Dense Retrieval for a Product Catalogue
A side-by-side evaluation of keyword search and embedding-based search on a realistic product dataset, showing where each approach wins and how hybrid search splits the difference.
The algorithms behind search and language — explained visually.
NLP and information retrieval are full of ideas that are easy to state but hard to hold in your head. This reference covers the terms, techniques, and papers that practising engineers actually encounter — with step-through animations built for the moment an algorithm finally clicks.
An inverted index merge, a dynamic programming traceback, a sliding n-gram window — each one clicks into place the moment you see it move. Every concept that benefits from animation has a step-through you can pause, rewind, and replay.
Written for engineers building search systems, working with language models, or filling the gaps that most NLP courses skip over.
Before you tune a search system you need a way to know whether your changes made things better or worse. This guide shows you how to build a hand-crafted relevance judgement set — a spreadsheet of queries, documents, and expected rankings — and how to use it as a repeatable baseline.
Read more →A side-by-side evaluation of keyword search and embedding-based search on a realistic product dataset, showing where each approach wins and how hybrid search splits the difference.