Creating synthetic data for replication & privacy protection using generative adversarial networks.

Christian Arnold, PhD, Lecturer in Politics at Cardiff University, discusses his research using generative adversarial networks (GANs) to create synthetic data for replication and privacy protection, including how GANs work, issues addressed by GANs, recommendations to students interested in researc...

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Bibliographic Details
Other Authors:	Arnold, Christian (Academic.)
Format:	Video
Language:	English
Language Notes:	Closed-captions in English.
Published:	London : SAGE Publications Ltd, 2019.
Subjects:	Social sciences > Statistical methods. Data protection. Sciences sociales > Méthodes statistiques. Protection de l'information (Informatique)
Online Access:	Connect to this streaming video

Description
Summary:	Christian Arnold, PhD, Lecturer in Politics at Cardiff University, discusses his research using generative adversarial networks (GANs) to create synthetic data for replication and privacy protection, including how GANs work, issues addressed by GANs, recommendations to students interested in research using GANs, and why social scientists should be working with big data and using data science methods.
Physical Description:	1 online resource (1 video file (00:12:49)) : sound, colour
ISBN:	9781526496300 1526496305