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.
ULMFiT is a technique in Natural Language Processing (NLP) that enables transfer learning for NLP tasks. It involves pretraining a language model on a…