January 2018
Beginner to intermediate
284 pages
8h 35m
English
For the Continuous Bag-of-Words (CBOW) model, the idea is even more straightforward, because the model uses the surrounding context to predict the target word. The inputs are still basically the surrounding context with a fixed window size, C; the difference is that we aggregate them (adding their one-hot encoding) first, then input to the neural network. These words will then be processed through the middle layer, and the output is the target word in the center.
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