629: Software for Efficient Data Science
Super Data Science: ML & AI Podcast with Jon Krohn
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Are There Any Challenges for Data Preparation?
Most of us who are working in industry, you're going to be working with data that wasn't collected for your models. You at least need to have some sort of definition or someone to explain how that data was created and the assumptions behind how it was put together. So I think there's probably the first most fundamental thing is actually making sure that the fields that you've collected are measuring what you think they measure.
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