Natural Language Models

Monitoring your Language Model might give you the feedback to further improve on performance and usage.

Deploying your Language Model might be a recurrent building block fro DevOps in a larger pipeline.

Explaining the outcomes of your Language Model is needed to prevent distrust and increase transparency.

Evaluating the quality of a Language Model should be done by comparisons based on the right metrics for your model type.

Training Language Models should start with a simple baseline and be improved with more complex techniques.