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.
One-Shot learning is an AI approach that enables models to learn from only one or a few examples. This approach is advantageous in tasks…