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In this tutorial, the presenter explains how to create sentence embeddings and apply them for tasks such as sentence similarity, semantic search, and clustering. Sentence embedding is defined as a natural language processing technique that transforms text or sentences into vector representations. The tutorial illustrates how converting sentences into numerical forms allows for mathematical operations to assess similarities between sentences and cluster them based on their numerical representations. The goal is to ensure that semantically similar sentences in the real world are also close in their vector representation, facilitating effective comparisons and analyses.
