Vector Databases in Production: Chroma, FAISS, pgvector
«Vector Databases in Production: Chroma, FAISS, pgvector» è un corso online di RAG e AI engineering di livello intermedio, tenuto da InsightLearn Curated AI su InsightLearn. Il percorso comprende 8 lezioni organizzate in 3 sezioni, per una durata complessiva di 9h 0m. Compare and deploy vector databases for AI applications: Chroma, FAISS, pgvector, and managed solutions.
- Docente: InsightLearn Curated AI
- Categoria: RAG e AI engineering
- Livello: intermedio
- Durata: 9h 0m
- Accesso: gratuito in questa fase di validazione, in cambio di un feedback al termine
- Certificato: certificato di completamento verificabile online
Descrizione del corso
InsightLearn è in fase di sviluppo (work in progress): i contenuti di questa pagina sono pubblicati esclusivamente a fini di verifica e test.
A practical comparison of vector database options for production RAG systems. Covers embedding fundamentals (dimensions, distance metrics), Chroma (local and client-server mode), FAISS (flat, IVF, HNSW index types), pgvector (SQL + vector in PostgreSQL), Qdrant and Weaviate managed offerings, index selection criteria (recall vs speed vs cost), filtering strategies, multi-tenancy patterns, and migration between vector stores.
Cosa imparerai
- Curated from public resources. Compare and deploy vector databases for AI applications: Chroma, FAISS, pgvector, and managed solutions.
Programma del corso
- Embeddings 101: dimensions, distance metrics, normalization (25 min)
- ANN index types: flat, IVF, HNSW, PQ (30 min)
- Chroma: setup, collections, and metadata filtering (32 min)
- FAISS: index selection, GPU acceleration, serialization (35 min)
- pgvector: vector search inside PostgreSQL (28 min)
- Multi-tenancy and namespace isolation in vector DBs (28 min)
- Hybrid filtering: metadata + vector similarity (22 min)
- Vector DB migration: from Chroma to Qdrant/Pinecone (30 min)
Dalle lezioni
Estratto della trascrizione di «Embeddings 101: dimensions, distance metrics, normalization»
Welcome to this lecture of the course of vector-tabase in production. Chroma, Faiz, Vector. In this session we will explore embeddings 101. Dimensions, Distance Metrics, Normalization. We will start with the fundamental concepts and the theoretical principles of the base. We will then see practical applications and almost real uses in the development world. Let's analyze embeddings. and the best practices in the sector. At the end of this lesson, you will be able to automatically apply the Embedding 101 techniques in your projects. We will start with the fundamental concepts and the basic theory principles. We will then see practical applications and almost practical uses in the development world. We will analyze the examples and the best practices in…
Estratto della trascrizione di «ANN index types: flat, IVF, HNSW, PQ»
Welcome to this lecture of the course of Vector Database in Production. What are you doing, Vector? In this session we will explore the INDECTIPES. Flat, IVE, HNS2PV, PQ. We will start with the fundamental concepts and the theoretical principles of the base. We will then see practical applications and almost one of the real ones in the world of development. We will analyze them. and the best practices of the sector. At the end of this lesson, you will be able to apply autonomously the techniques of ANN index to your projects. We will start with the fundamental concepts and the basic theoretical principles. We will then see practical applications and almost real uses in the world of development.…
Estratto della trascrizione di «Chroma: setup, collections, and metadata filtering»
Welcome to this lecture of the course of Vector Database in Production. In this session, we will explore Vector. Setup, Corrections, and Metadata Filtering. We will start with the fundamental concepts and the basic principles. We will then see practical applications and almost universal applications in the world of the universe. We will analyze them in concrete elements. of the sector. At the end of this lesson, you will be able to apply autonomously the techniques of your projects. We will start with the fundamental concepts and the basic theoretical principles. We will then see practical applications and almost real ones in the world of development there. We will analyze the concrete times and the techniques of the sector. At…
Altri corsi di RAG e AI engineering
- Agentic AI Patterns: ReAct, Plan-and-Execute, and Multi-Agent
- AI Engineering: Building Production LLM Applications
- AI Safety: Alignment, Red-Teaming, Responsible Deployment
- Fine-Tuning LLMs: LoRA, QLoRA, and Full Fine-Tuning
- Function Calling & Tool Use: Multi-Model Production Patterns
- LangSmith: Tracing, Debugging, and Monitoring LLM Apps
Domande frequenti
Quanto dura il corso Vector Databases in Production: Chroma, FAISS, pgvector?
Il corso dura 9h 0m in totale, con 8 lezioni suddivise in 3 sezioni, da seguire online al proprio ritmo.
Serve esperienza pregressa?
Il corso è di livello intermedio e non indica requisiti specifici di ingresso.
Il corso rilascia un certificato?
Sì: al completamento del corso ricevi un certificato di completamento verificabile online.