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.
Knowledge Graphs are a structured representation of knowledge that captures relationships between entities. They organise information in a way that allows machines to understand…