Natural language processing
Natural language processing (NLP)
The Classical NLP consists of creating a pipeline using processors to create annotations from text files.
Below is an example of a few processors.
- Convert a paragraph of test or a file into an array of words.
- Part-of-speech annotation
- Named Entity Recognition
Datasets and Challenges
The Stanford Question Answering Dataset. There are two versions of this dataset, 1.1 and 2.0.
Attention is all you need paper
A neural network architecture by Google. It is currently the best at NLP tasks and has mostly replaced RNNs for these tasks.
- Guides and explanations
- A Lite BERT for Self-supervised Learning of Language Representations
This is a parameter reduction on Bert.