Summary
In this chapter, you learned how to manage spaCy projects with Weasel. First, you cloned a project template from spaCy’s repository and ran it on your machine. Then, you used this same project structure to train a model for a dataset. After that, you saw how GitOps can address some data science and ML challenges and used DVC to register the model we’ve trained to share it with teammates or add a deploy setting to it. The goal of this chapter was to teach you how to manage NLP projects in a production setting.
In the next chapter, we will explore how to train a model for coreference resolution. This will involve understanding what coreference resolution is, why it is important in NLP, and how to implement it using spaCy.
