Rob de Wit
Rob is a developer advocate at Iterative AI. He’s got a background in information sciences, and experience in data analytics and engineering. Right now he’s learning a whole lot about MLOps and exploring how people can adopt a collaborative, experiment-driven approach to ML projects.
In machine learning projects we need to experiment in order to find and maintain the best-performing model. While we can do initial prototyping in a Notebook, eventually we need to move towards more structured experiment tracking to facilitate reproducibility of our experiments.
The open-source DVC library aims to tackle this problem through a Git-based approach to versioning data and artifacts. In this talk we will explore how DVC works, how we can apply it to conduct ML experiments, and how we can use it to become a great Pokémon trainer.