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.
Uncertainty in AI refers to the unpredictability or lack of full knowledge about a situation or outcome. AI models often encounter uncertainties due to…