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Building and testing machine learning models requires access to large and diverse data.
Data scientists will learn how Synthetic Data generation provides a way to make suc.
But where can you find usable datasets without running into Privacy issues? This Practical book introduces techniques for generating Synthetic data--fake Data generated from real data--so you can perform secondary analysis to do research, understand customer behaviors, develop new products, or generate new revenue.
Building and testing machine learning models requires access to large and diverse data
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