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Word2Vec Tutorial Part 2 - Negative Sampling · Chris McCormick

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In part 2 of the word2vec tutorial (here’s part 1), I’ll cover a few additional modifications to the basic skip-gram model which are important for actually making it feasible to train.

Word2Vec Tutorial Part 2 - Negative Sampling 11 Jan 2017 In part 2 of the word2vec tutorial (here’s part 1 ), I’ll cover a few additional modifications to the basic skip-gram model which are important for actually making it feasible to train. When you read the tutorial on the skip-gram model for Word2Vec, you may have noticed something–it’s a huge neural network! In the example I gave, we had word vectors with 300 components, and a vocabulary of 10,000 words. Recall that the neural network had two weight matrices–a hidden layer and output layer. Both of these layers would have a weight matrix

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