Materials on AI, Python, Git, SQL, Web/API, SAP/ERP, statistics and time series: explanations, examples, practical tips, sources and applicability limits.
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A guide to setting up multimodal search in Azure AI Search using vectorization of text and images. Describes steps for creating an index, selecting models (e.g., CLIP), methods for generating embeddings, and executing hybrid queries to improve relevance.
Explore the principles of semantic search, its reliance on embeddings, and the reasons why text that appears similar might not provide the desired answer. Learn about vector search, hybrid search, and their applications in information retrieval.
Step-by-step guide to creating an index, generating embeddings, and executing hybrid queries that combine full-text and vector search using Azure AI Search.