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.
Incremental Learning is an AI technique that allows models to continuously learn from new data without retraining from scratch. Instead of training the model…