Practical Synthetic Data Generation
Practical Synthetic Data Generation Building and testing machine learning models requires access to large and diverse data. This practical book introduces techniques for generating synthetic…
Specifikacia Practical Synthetic Data Generation
Practical Synthetic Data Generation
Building and testing machine learning models requires access to large and diverse data. 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.Data scientists will learn how synthetic data generation provides a way to make such data broadly available for secondary purposes while addressing many privacy concerns. But where can you find usable datasets without running into privacy issues?
And business leaders will see how synthetic data can help accelerate time to a product or solution.This book describes:Steps for generating synthetic data using multivariate normal distributions Methods Analysts will learn the principles and steps for generating synthetic data from real datasets.
Practical Data Privacy
Practical Data Migration