It is referred to as global vectors because the global corpus statistics were captured directly by the model. It finds great performance in world analogy and named entity recognition problems. The rows represent each document, the columns represent the vocabulary, and the values of tf-idf(i,j) are obtained through the above formula. This matrix obtained can be used along with the target variable to train a machine learning/deep learning model. Word embedding or word vector is an approach with which we represent documents and words. It [...]

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