Balancing Privacy and the Broad Availability of Data
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Building and testing machine learning models requires access to large and diverse data. But where can you find usable datasets without running into privacy issues? This practical book introduces techniques for generating synthetic data so you can perform secondary analysis to do research, understand customer behavior or develop new products
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