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    Building Applications with Vector Databases
    Featured

    DeepLearning.AI course teaching six practical vector database applications using Pinecone, including RAG for LLMs, recommender systems, and hybrid search combining images and text.

    Vector Database Fundamentals (Coursera)

    IBM's comprehensive specialization providing job-ready vector database skills in one month, covering foundational knowledge for LLM-powered AI similarity searches, available for free enrollment.

    LangChain & Vector Databases in Production

    Free comprehensive course from Activeloop with 60+ lessons and 10+ practical projects, teaching production-ready LLM applications with vector databases, trusted by 10,000+ engineers.

    Introduction to Information Retrieval

    Foundational IR textbook that includes content on vector‑space models and retrieval, providing essential background for understanding vector search and hybrid retrieval in modern vector databases.

    Machine Learning Crash Course: Embeddings

    Module of Google’s Machine Learning Crash Course that explains word and text embeddings, how they are obtained, and the difference between static and contextual embeddings, giving essential background for using vector representations in vector databases and similarity search systems.

    VectorHub

    VectorHub is a resource and learning platform for developers and ML architects interested in integrating vector retrieval and search capabilities into their machine learning stacks, directly supporting vector database adoption and usage.

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    All product names, logos, and brands are the property of their respective owners. All company, product, and service names used in this repository, related repositories, and associated websites are for identification purposes only. The use of these names, logos, and brands does not imply endorsement, affiliation, or sponsorship. This directory may include content generated by artificial intelligence.
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