Transforming a Jupyter Notebook into a Reproducible Pipeline for ML Experiments

This talk shows data scientists how to turn a notebook prototype into a reproducible pipeline for machine-learning experiments. Using a text-to-image project, it covers splitting a notebook into modules, running experiments with Git and DVC, and comparing results.