Machine Learning Mastery: semantic search with embeddings instead of keywords

Keyword search fails in real-world scenarios: the user searches by meaning, while the system searches literally. Machine Learning Mastery shows how to fix this problem in Python. The solution has two parts: LLM embeddings capture the semantic meaning of the query, and metadata helps filter and rank results contextually. The result is intelligent search that understands user intent.