Today's topic tackles my consistent frustrations with the Data Science community and how they apply machine learning algorithms and other tools to data without fully understanding the rest of the context. While this problem isn’t constrained to Data Science specifically, this discipline does lead the pack in examples. To understand this problem we’ll focus on three things that have been forgotten. The first thing forgotten is the history of where Data Science came from and the second two things forgotten derives from the first, and leads to the majority of the issues with applying Data Science solutions.

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