Learn how to implement NER-powered semantic search in Python through this comprehensive tutorial video. Explore the process of combining semantic search with keyword filtering using Pinecone, allowing for more precise and meaningful search results. Discover how to prepare datasets, create NER entities using Transformers, generate embeddings with Sentence Transformers, and utilize Pinecone Vector Database for efficient indexing and querying. Follow along as the instructor demonstrates indexing a full Medium articles dataset and making queries to Pinecone. Gain valuable insights into advanced search techniques and their practical applications in natural language processing.

Syllabus

NER Powered Semantic Search
Dependencies and Hugging Face Datasets Prep
Creating NER Entities with Transformers
Creating Embeddings with Sentence Transformers
Using Pinecone Vector Database
Indexing the Full Medium Articles Dataset
Making Queries to Pinecone
Final Thoughts