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.
Robotics involves designing, building, and programming machines that can perform tasks autonomously or interact with humans. By combining AI with physical systems, businesses can…