Lecture
This lecture covers the implementation of a basic search engine using word embeddings, where students are tasked with visualizing, interpreting, and computing cosine similarity to rank words based on a given input term. The exercise involves aggregating word embeddings for tweets and queries, and ranking tweets based on cosine distances.