We were working on a project with a domain expert recently and felt there could be learnings that are relevant to the community we could share.<p>In our case, the domain expert was a dentist who reached out to us to help him create a machine learning model that would segment teeth in panoramic X-rays. He had some data pre-labeled, but the vast majority of his dataset was unlabeled.<p>Since labeling these X-rays is a time consuming process and requires domain knowledge, we decided to use Active Learning.<p>Following our success in creating an Active Learning pipeline in a Jupyter Notebook using Data Engine, we created a new Tooth Fairy project, which expands on that and brings even more capabilities into the notebook.<p>https://dagshub.com/blog/active-learning-with-domain-experts-a-case-study/<p>Check out our post and learn:
* Why and when you should use Active Learning
* How to efficiently work with domain experts (and mistakes to avoid!)
* What a real use-case Active Learning pipeline looks like, by checking out the accompanying repo<p>Curious to get your input on this