Summary
Chapters
Video Info
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.
-
Chapter 1: How Did You Become Interested in Machine Learning Methods and What Research Have You Been Working on Recently?
icon angle down -
Chapter 2: How Do Generative Adversarial Networks Work in Practice, and How Will Your Work Improve Replication?
icon angle down -
Chapter 3: How Can we Understand Generative Adversarial Networks in a More Intuitive Way?
icon angle down -
Chapter 4: What Kind of Questions Have You Been Able to Answer Using Generative Adversarial Networks?
icon angle down -
Chapter 5: What Would You Recommend to Students Willing to Explore This Research Method Further?
icon angle down -
Chapter 6: Why Should Social Scientists Work With Big Data and Data Science Methods?
icon angle down