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.
Probabilistic Graphical Models is a type of statistical model used in Machine Learning and Artificial Intelligence. They represent complex relationships between variables through graphs…