The Machine Learning Angle for Open Source Science

Reproducibility is a fundamental aspect of machine learning research. However, the extensive use of Jupyter Notebooks for Machine Learning experiments has confounded challenges in ensuring research reproducibility within the domain of machine learning. This session aims to discuss an extensible approach to reproducible machine learning, using cookiecutters for code structure, MLFlow for experiment tracking and DVC for data versioning.

Jinen Setpal
Jinen Setpal
ML Engineer @ DagsHub

Research under Interpretable Domain Generalization.