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.
Decision networks, also known as Probabilistic Graphical Models, are a type of AI model that represents uncertain knowledge using a graph structure. Decision Networks…