Introduction to Embeddings with the OpenAI API

Course overview

Technical exploration of embeddings with the OpenAI API: definitions, creation, enrichment and practical applications. Covers semantic search, similarity sorting, vector enrichment and vector databases including ChromaDB.

What an embedding is and how embeddings represent text for downstream tasks.

How to create embeddings and enrich them to improve semantic search and similarity measures.

Methods for similarity sorting and indexing for search and recommendation scenarios.

Overview of vector databases: selecting a solution, handling metadata and building vector stores with ChromaDB.