Hello, I watched the video 5 from fast.ai course Part 1 about collaborative filtering.
I have understood the concept, but when I want to use the model in the real situation, when there is a new user, I have to recommend the movies according to the ratings he/she made. Similar for new movie.
Many deep learning models are feed-forward, so when I give it a new data, it pops out a result(prediction, classification, etc). But the model from lecture 5 first need the embedding vector for a new user or new movie first. Is there a way the collaborative filtering handles this new data issue, or should I use another model?