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added descriptions to each page
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title: "Day 5: Advanced APIs"
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description: Learn advanced Qdrant APIs, including multivectors and the Universal Query API, to power hybrid retrieval, late interaction models, and recommendation systems with high accuracy and flexibility.
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isLesson: true
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weight: 60
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title: Multivectors for Late Interaction Models
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title: "Multivectors for Late Interaction Models"
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description: Learn how Qdrant supports late interaction models like ColBERT and ColPali using multivectors for token-level precision, enabling fine-grained, context-aware text and visual document retrieval.
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weight: 2
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title: "Project: Building a Recommendation System"
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description: Build a hybrid AI recommendation system with Qdrant’s Universal Query API—combining dense, sparse, and multivector retrieval, ColBERT reranking, and RRF fusion in one atomic query.
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weight: 5
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title: The Universal Query API
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title: "The Universal Query API"
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description: Learn how to run dense, sparse, and ColBERT multivector retrieval with Qdrant’s Universal Query API—fusing, filtering, and reranking results in a single atomic request.
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weight: 3
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title: "Demo: Universal Query for Hybrid Retrieval"
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description: Build a hybrid research discovery system using Qdrant’s Universal Query API—combine dense, sparse, and ColBERT vectors for semantic, keyword, and reranked retrieval in one query.
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weight: 4
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