Data Science, Machine Learning, NLP, Word Embeddings, AI.
need to represent each word with a one-hot encoding. We would first look up the index of the first word, “the”, and find that its index in our 10,000-long vocabulary list is 8676. We could then represent the word “the” using a length 10,000 vector, where every entry is a 0 aside from the entry at