Triplet loss is a loss function commonly used in machine learning, particularly in tasks involving similarity learning, such as face recognition, image retrieval, and metric learning. The concept is designed to optimize the embeddings of data points in such a way that similar points are brought closer together while dissimilar points are pushed apart in the embedding space. ### Key Components of Triplet Loss 1.
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