This is part 1/2 for training word embeddings. In this part, we only understand the theory behind training word embeddings. In the next part, we will code the same in python.

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This happens because any bias in the articles that make up the Word2vec corpus is inevitably captured in the geometry of the vector space. Bolukbasi and co despair at this.