GloVe (Global Vectors for Word Representation) is an unsupervised learning algorithm for obtaining vector representations of words. It maps words into a meaningful space where the distance between words is related to semantic similarity. GloVe achieves this by aggregating global word-word co-occurrence statistics from a corpus. The resulting word vectors can then be used in various downstream NLP tasks, such as sentiment analysis, named entity recognition, and machine translation. GloVe is commonly used to initialize word embeddings in deep learning models.
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