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.
An algorithm is a set of rules and instructions that guide AI systems in solving problems or making decisions. Algorithms process data, analyse patterns,…