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.
Explainable Artificial Intelligence focuses on developing AI systems that can provide understandable explanations for their decisions and behaviours. Transparent and interpretable AI models are…