Word embedding is a technique used in natural language processing (NLP) to represent words as dense vectors in a high-dimensional space. These word vectors capture semantic and syntactic relationships between words, and are used as inputs to many NLP tasks such as text classification, sentiment analysis, and machine translation. The…