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.
Fuzzy Logic is a mathematical framework that deals with uncertainty and imprecision. By assigning degrees of truth to statements, Fuzzy Logic allows businesses to…