Reproducibility: The Life and Risks of a Model

Posted on in Presentations

Analytics are becoming ubiquitous in the ever-increasing world of data. Often, those analytics are implemented without thorough consideration of the life and the risks of the model employed. This session will explore enabling reproducibility and repeatability in data science, the life cycle of a model, what is missing in typical models of today, and how to ensure a healthy and reliable life of a model.

Pre-Requisites: General knowledge about security analytics is helpful but not required.

Celeste Fralick


Chief Data Scientist, McAfee

Protecting Data & the Supply Chain Ecosystem Hackers & Threats Machine Learning & Artificial Intelligence

hackers & threats big data analytics artificial intelligence & machine learning anti-malware



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