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.
Edge Computing brings computing resources closer to the source of data generation, reducing latency and improving response times. By processing and analysing data locally…