Machine Learning, Naturallanguageprocessing, Artificial Intelligence, NLP, AI.
weights, rather than all of them for each training sample. We do this by slightly modifying our problem. Instead of trying to predict the probability of being a nearby word for all the words in the vocabulary, we try to predict the probability that our training sample words are neighbors or not.