As we have seen in the previous section, while BOW and TF-IDF can create numeric vectors for documents, the length of the vectors is usually quite large as it depends on the size of the vocabulary (number of n-grams).

Could we assign a vector in “low dimension”, encoding the “semantic” of a word (or document)?

SKIPGRAM


**Continuous Bag of Words Mode (**CBOW)


CBOW vs SKIPGRAM


Training or Pre-trained models


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