GloVe
GloVe (Global Vectors for Word Representation) is an unsupervised learning algorithm for obtaining vector representations (embeddings) of words from large text corpora. It combines global matrix factorization and local context window methods to capture semantic and syntactic word relationships, producing dense word vectors that are widely used in natural language processing tasks.
Developers should learn GloVe when working on NLP projects that require word embeddings for tasks like text classification, sentiment analysis, or machine translation, as it efficiently captures word meanings from co-occurrence statistics. It is particularly useful for applications where pre-trained embeddings can boost performance without extensive training data, such as in academic research or industry NLP pipelines.