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.
Sentiment Analysis is an AI technique that analyses emotions and opinions expressed in text data. Sentiment analysis can classify text as positive, negative, or…