- “The most important question in data science is not which machine learning algorithm to choose or even how to clean your data. It is the questions you need to ask before even one line of code is written: What data do you choose and what questions do you choose to ask of that data?
- So while parts of core machine learning are automated (in fact, we even teach some of the ways to automate those workflows), the data munging, data cleaning and feature engineering (which comprises 90% of the real work in data science) cannot be safely automated away.”
Will automation eliminate data science positions?
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