Word embeddings in NLP
We will discuss word embeddings this week. Word embeddings represent a fundamental shift in natural language processing (NLP), transforming words into dense vector representations that capture semantic and syntactic meaning. Moving beyond sparse, context-agnostic methods such as bag-of-words and one-hot encoding, modern embedding techniques (from Word2Vec to transformers) enable machines to capture linguistic relationships and…