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Vector Databases
Learning Outcomes
- Vector database architecture and selection
- Embedding models and generation
- Similarity search and retrieval
- Indexing and optimization strategies
- Scaling vector operations
Ref - Vector Databases: Complete Guide to Similarity Search and Retrieval
Introduction
Vector databases are specialized database systems designed to store and efficiently query high-dimensional vectors, making them crucial for AI/ML applications, particularly in similarity search and retrieval tasks.
Core Concepts
- Understanding Vector Databases - Deep dive into vector databases, their architecture, and popular solutions
- Similarity Search - Comprehensive guide to similarity search mechanisms and distance metrics
- Semantic Vs Similarity Search - Understanding the difference between semantic and similarity search