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.
Reinforcement Learning is a branch of AI that focuses on training agents to make decisions through trial and error in a specific environment. By…