2 Getting started with human-in-the-loop machine learning
This chapter covers
- Ranking predictions by model confidence to identify confusing items
- Finding unlabeled items with novel information
- Building a simple interface to annotate training data
- Evaluating changes in model accuracy as you add more training data
For any machine learning task, you should start with a simple but functional system and build out more sophisticated components as you go. This guideline applies to most technology: ship the minimum viable product (MVP) and then iterate on that product. The feedback you get from what you ship first will tell you which pieces are the most important to build out next.
This chapter is dedicated to building your first human-in-the-loop ...
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