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.
Ensemble Learning involves combining multiple Machine Learning models to achieve superior performance and accuracy. By leveraging the “wisdom of the crowd,” Ensemble Learning mitigates…