Part 4: Getting Started with Data-Centric ML
By now you may have realized that shifting to a data-centric approach to ML involves not just adapting your own ways of working, but also influencing those around you – a task that’s far from simple. In this part, we explore both the technical and non-technical hurdles you might encounter during the development and deployment of models, and reveal how adopting a data-centric approach can aid in overcoming these obstacles.
This part has the following chapter:
- Chapter 10, Kick-Starting Your Journey in Data-Centric Machine Learning