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Machine learning techniques for data cleaning


PyData Chicago 2016


Often, the most interesting datasets - data about people and organizations - are the messiest and most difficult to analyze. When data comes from multiple sources, or when data is entered manually, variation & ambiguity are inevitable. Learn about ways to infer structure and relationships in messy data, using open source Python libraries.

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