In this recipe, we will implement the CBOW method of word2vec. It is very similar to the Skip-Gram method, except we are predicting a single target word from a surrounding window of context words.
In the previous example, we treated each combination of window and target as a group of paired inputs and outputs, but with CBOW we will add the surrounding window embeddings together to get one embedding to predict the target word embedding:
Figure 5: A depiction of how the CBOW embedding data is created out of a window on an example sentence (window size = 1 on each side)
Most of the code will stay the same, except we will need to ...
