The TDDA library has discover functionality, which will construct a set of constraints that are true for your input data. If you verify your input data using the constraints generated from it, it will pass. The more important thing to check is the other side of it, where if actually you fed it bad data then you'll get either missing constraints or constraints that are too loose.
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Nick Radcliffe, data scientist and entrepreneur, talks to us about the importance of test your data. As software engineers we are familiar with test driven development. Test driven data analysis puts the same emphasis on validating and testing data for your AI app. We also dive into the Python library of the same name tdda.
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