<ul><li>Embedding models are used in machine learning to convert categorical data into a continuous vector space.</li><li>Embedding models enhance search functionality by understanding the semantic meaning of queries and documents.</li><li>Word2Vec is a popular embedding model that learns word representations based on local contexts.</li><li>Searching with embedding models involves calculating cosine similarity between query and document vectors.</li></ul>

Understanding embedding models and how to use them in search

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