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In this tutorial, the presenter explains how to create sentence embeddings and their applications, including sentence similarity, semantic search, and clustering. Sentence embeddings are a natural language processing technique that transforms text or sentences into vector representations. This transformation allows for various mathematical operations to assess the similarity between sentences. By representing sentences numerically, one can determine semantic similarities and cluster sentences accordingly. The tutorial emphasizes that effective embeddings will reflect real-world semantic relationships between sentences, enabling better analysis and application in different NLP tasks.
