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.
Variational Autoencoders are a type of generative model used in unsupervised learning. VAEs learn a low-dimensional representation of input data and can generate new…