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Description
Vector databases are the infrastructure backbone of AI applications. This course opens the black box: you’ll understand the math behind similarity search, benchmark the top solutions, and build production-ready vector search systems optimized for speed and accuracy. Covers Pinecone, Weaviate, Qdrant, and pgvector in depth.
What’s Inside:
- How Vector Search Works
- Euclidean vs Cosine Similarity
- HNSW and IVF Indexing
- Pinecone Deep Dive
- Weaviate Deep Dive
- Qdrant and Chroma Comparison
- Metadata Filtering at Scale
- Namespace and Index Design
- Batch Uploading Strategies
- Latency and Throughput Tuning
- Monitoring in Production
- Project: Semantic Product Search Engine
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