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October 24-26 | Monterey, California
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Wednesday, October 25 • 11:40am - 12:10pm
The Machine Learning Angle for Open Source Science - Jinen Setpal, Purdue University

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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.
Speakers
avatar for Jinen Setpal

Jinen Setpal

Undegraduate Student, Purdue University
I am an undergraduate studying towards my B.Sc in Data Science at Purdue University. My research interests lie at the intersection of Machine Learning Theory and Interpretability; specifically, leveraging intuitive biases to develop techniques for interpretable domain generalization... Read More →

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Wednesday October 25, 2023 11:40am - 12:10pm PDT
Regency Ballroom VI (Regency Conference Center)
  Best Practices in Open Source Development / Lessons Learned
  • Slides Included Yes