Word Embeddings are a technique in NLP that represent words as continuous vectors in a high-dimensional space. These vectors capture semantic and syntactic relationships between words. Word embeddings are useful for tasks such as language translation, sentiment analysis, and document clustering.
Natural Language Processing involves the interaction between computers and human language, enabling machines to understand, interpret, and generate human language. It powers applications like…