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Medical Search Engine with SPLADE + Sentence Transformers in Python

James Briggs via YouTube

Overview

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This hands-on course builds a medical question-answering search engine in Python using PubMed QA data, SPLADE sparse embeddings, Sentence Transformers dense embeddings, and Pinecone hybrid search. It covers preprocessing, vector creation, index construction, and hybrid queries.

Syllabus

Hybrid search for medical field
Hybrid search process
Prerequisites and Installs
Pubmed QA data preprocessing step
Creating dense vectors with sentence-transformers
Creating sparse vector embeddings with SPLADE
Preparing sparse-dense format for Pinecone
Creating the Pinecone sparse-dense index
Making hybrid search queries
Final thoughts on sparse-dense with SPLADE

Taught by

James Briggs

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