Instance-Based Learning is an AI approach where models make predictions based on similarity to previously seen examples. Instead of generalising from a predefined set of rules, Instance-Based Learning examines specific instances and their characteristics. This approach is effective in tasks such as pattern recognition and recommendation systems.
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…