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.
Automation involves the use of technology, including AI, to perform tasks and processes with minimal human intervention. By automating repetitive or time-consuming tasks, businesses…