The first algorithm we’ll talk about is known as the skip-gram algorithm, which is a type of Word2vec algorithm. As we have discussed in numerous places, the meaning of a word can be elicited from the contextual words surrounding it. However, it isn’t entirely straightforward to develop a model that exploits this way of learning word meanings. The skip-gram algorithm, introduced by Mikolov et al. in 2013, is an algorithm that exploits the context of the words in a written text to learn good word embeddings.

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