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YouTubeProfessor Py: Information Retrieval with Python
BM25 in Python: Rank Better with Boosts and Priors that Reorder
Understand search scores with BM25 and boosts—learn when to use it over dense embeddings. Build a Python pipeline for tokenization, term counts, simple IDF, BM25 (k1, b), query boosts, and document priors to rank top results fast. We use pure Python with regex tokenization, length normalization, and evaluate with NDCG—fast, interpretable ...
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