{"product_id":"practical-synthetic-data-generation","title":"Practical Synthetic Data Generation","description":"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-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\n\nData scientists will learn how synthetic data generation provides a way to make such data broadly available for secondary purposes while addressing many privacy concerns. Analysts will learn the principles and steps for generating synthetic data from real datasets. And business leaders will see how synthetic data can help accelerate time to a product or solution. \n\nThis book describes:\nSteps for generating synthetic data using multivariate normal distributions\nMethods for distribution fitting covering different goodness-of-fit metrics \nHow to replicate the simple structure of original data \nAn approach for modeling data structure to consider complex relationships\nMultiple approaches and metrics you can use to assess data utility\nHow analysis performed on real data can be replicated with synthetic data\nPrivacy implications of synthetic data and methods to assess identity disclosure","brand":"O'Reilly Media","offers":[{"title":"Default Title","offer_id":54218030055768,"sku":"9781492072744","price":65.99,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0278\/1295\/4195\/files\/9781492072744.jpg?v=1777052748","url":"https:\/\/agendabookshop.com\/products\/practical-synthetic-data-generation","provider":"Agenda Bookshop","version":"1.0","type":"link"}