Build a ColBERT‑Style Late‑Interaction Retriever in Pure Python
Learn how to construct a fast, vector‑less late‑interaction retriever and inverted index using only standard Python, and why it impresses hiring managers.
Information Retrieval
Mastering BM25: How to Tune Search Relevance in Large‑Scale Indexes
A hands‑on guide to adjusting BM25 k1 and b, handling document length normalization, and scaling BM25 for low‑latency search at scale.
Deep Dive into BM25+: Tuning Parameters for Large‑Scale Enterprise Search
BM25+ extends classic BM25 with term frequency saturation and document length normalization. This guide walks you through parameter selection, real-world tuning, and production patterns for enterprise search.
Build a RAG Pipeline with From-Scratch BM25: A Hands-On Portfolio Project
A hands-on guide to building a Retrieval-Augmented Generation pipeline with a from-scratch BM25 scorer. Covers architecture, real Python code, testing, and a senior-level roadmap for extending it into a production-grade system.
Implementing BM25 Ranking with Lucene: Precision, Tuning, and Production Trade-offs
BM25 is the default ranking function in Lucene and Elasticsearch, but most engineers never tune its parameters. This post unpacks the algorithm’s internals, practical configuration levers, and the production trade-offs that separate adequate search from great search.