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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.
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