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How can we use neural networks to create meaningful representations of words? The bag-of-words is limited in its ability to characterize text, because it does not utilize word context. In this part, we study word embeddings, which were among the first attempts to use neural networks to develop numerical representations of text that incorporate context. We learn how to use the package gensim to construct and explore word embeddings of text.