#Vector Database

LLMs don't know what they weren't trained on. Here's how RAG fixes that — walking through the complete pipeline from document ingestion to chunking, embedding, vector storage, retrieval, and generation with real Python and TypeScript examples.

How do computers understand that 'King' - 'Man' + 'Woman' = 'Queen'? We dive deep into the evolution of NLP embeddings, from One-Hot Encoding to Word2Vec and Transformer-based models. Learn about Vector Databases, Cosine Similarity math, and how RAG (Retrieval-Augmented Generation) is reshaping modern AI applications.