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.
Synthetic Data is artificially generated data that mimics real-world data. Synthetic data can be used to train Machine Learning models when real data is…