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In this tutorial, the presenter discusses creating and using sentence embeddings for various applications, including sentence similarity, semantic search, and clustering. Sentence embedding is explained as a natural language processing technique that converts text or sentences into vector representations. The tutorial highlights how these numerical representations allow for mathematical operations to determine the similarity between sentences and to cluster them based on their semantic meanings. The presenter emphasizes that effective embeddings will reflect real-world semantic similarities between sentences.
