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.
Neural Networks are a type of Machine Learning model inspired by the human brain. They are composed of interconnected nodes, or “neurons,” that process…