Data Science Operationalization: Ten Steps -- Pure AI

Data Science Operationalization: Ten Steps

Data science projects can be intimidating; after all, there are a lot of factors to consider. In today’s competitive environment, individual silos of knowledge will hinder your team’s effectiveness. Best practices, model management, communications, and risk management are all areas that need to be mastered when bringing a project to life.

This paper offers a discussion on topics ranging from Best Operating Procedures to Risk Management for unforeseen situations.

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