ULMFiT is a technique in Natural Language Processing (NLP) that enables transfer learning for NLP tasks. It involves pretraining a language model on a large corpus of text and then fine-tuning it on specific downstream tasks. ULMFiT has been successful in improving performance on tasks like text classification and sentiment analysis.
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…