Practical Synthetic Data Generation: Balancing Privacy and the Broad Availabilit

Description: Practical Synthetic Data Generation by Khaled El Emam, Lucy Mosquera, Richard Hoptroff 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 FORMAT Paperback LANGUAGE English CONDITION Brand New Publisher 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 revenueData 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. This book describes: Steps for generating synthetic data using multivariate normal distributions Methods for distribution fitting covering different goodness-of-fit metrics How to replicate the simple structure of original data An approach for modeling data structure to consider complex relationships Multiple approaches and metrics you can use to assess data utility How analysis performed on real data can be replicated with synthetic data Privacy implications of synthetic data and methods to assess identity disclosure" Author Biography Dr. Khaled El Emam is a senior scientist at the Childrens Hospital of Eastern Ontario (CHEO) Research Institute and Director of the multi-disciplinary Electronic Health Information Laboratory. Lucy Mosquera has a bachelors degree in Biology and Mathematics from Queens University and is a current graduate student in the department of statistics at the University of British Columbia. During her time at Queens, Lucy provided data management support on a dozen clinical trials and observational studies run through Kingston General Hospitals Clinical Evaluation Research Unit. Lucy has also worked on clinical trial data sharing methods based on homomorphic encryption and secret sharing protocols. At Replica Analytics, Lucy is responsible for developing statistical and machine learning models for data generation, and integrating subject area expertise in clinical trial data into synthetic data generation methods, as well as the statistical assessments of our synthetic data generation. Dr. Richard Hoptroff is a long term technology inventor, investor and entrepreneur. Details ISBN1492072745 Author Richard Hoptroff Pages 175 Year 2020 ISBN-10 1492072745 ISBN-13 9781492072744 Short Title Practical Synthetic Data Generation Language English Format Paperback Subtitle Balancing Privacy and the Broad Availability of Data Publication Date 2020-06-02 UK Release Date 2020-06-02 Place of Publication Sebastopol Country of Publication United States AU Release Date 2020-06-02 NZ Release Date 2020-06-02 US Release Date 2020-06-02 Imprint OReilly Media Publisher OReilly Media DEWEY 005.7 Audience Professional & Vocational We've got this At The Nile, if you're looking for it, we've got it. With fast shipping, low prices, friendly service and well over a million items - you're bound to find what you want, at a price you'll love! TheNile_Item_ID:128101372;

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