For NLP classification the current state of the art approach is Universal Language Model Fine-tuning (ULMFiT). ULMFiT is an effective transfer learning method that can be applied to any task in NLP, but at this stage we have only studied its use in classication tasks. The approach is described and analyzed in the Universal Language Model Fine-tuning for Text Classification paper by’s Jeremy Howard and Sebastian Ruder from the NUI Galway Insight Centre.

To learn to use ULMFiT and access the open source code we have provided, see the following resources:

More information: