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Vector Databases with Pinecone, Weaviate, and FAISS
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This book teaches vector databases from beginner to practical production level in simple language. It covers embeddings, similarity search, indexing, Pinecone, Weaviate, FAISS, and how to build retrieval systems and RAG backends with real examples.
Level: intermediateLanguage: EN EnglishRating: 0Reviews: 0
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01Chapter 1: Introduction to Vector Databases02Chapter 2: Embeddings, Similarity, and Distance Metrics03Chapter 3: Approximate Nearest Neighbor Search04Chapter 4: Data Modeling, Chunking, and Metadata05Chapter 5: Pinecone Fundamentals06Chapter 6: Weaviate Fundamentals07Chapter 7: FAISS Fundamentals08Chapter 8: Managed vs Self-Hosted Vector Systems09Chapter 9: Ingestion, Upserts, and Reindexing10Chapter 10: Hybrid Search, Filters, and Reranking11Chapter 11: Multitenancy, Namespaces, and Isolation12Chapter 12: Retrieval Evaluation and Search Quality13Chapter 13: Monitoring Latency, Recall, and Cost14Chapter 14: Security, Governance, and Backup Strategy15Chapter 15: Building RAG Services on Top of Vector Search16Chapter 16: Production Case Study and Next Steps17Appendix A: Commands and Workflow Cheat Sheet18Appendix B: Reference Architectures and Patterns19Appendix C: Common Mistakes and Fixes20Appendix D: Best Practices Summary
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