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.
Recommender Systems are AI systems that provide personalised recommendations to users based on their preferences and previous behaviour. These systems analyse large amounts of…