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While machine learning is integral to innumerable anti-abuse systems including spam and phishing detection, the road to reap its benefits is paved with numerous abuse-specific challenges. Drawing from concrete examples this session will discuss how these challenges are addressed at Google and provide a roadmap to anyone interested in applying machine learning to fraud and abuse problems.
Learning Objectives:
1: Learn how machine learning helps combat fraud and abuse.
2: Discover how to overcome challenges faced when using machine learning to anti-abuse.
3: Understand what the unsolved challenges are in the space. Link to presentation: https://docs.google.com/presentation/d/12rW6XjI539TPi8etehBF1Hm56GeCYyTZ37wjfuCE9xw/edit?usp=sharing
Learning Objectives:
1: Learn how machine learning helps combat fraud and abuse.
2: Discover how to overcome challenges faced when using machine learning to anti-abuse.
3: Understand what the unsolved challenges are in the space. Link to presentation: https://docs.google.com/presentation/d/12rW6XjI539TPi8etehBF1Hm56GeCYyTZ37wjfuCE9xw/edit?usp=sharing
Participants
Elie Bursztein
Participant
Google & DeepMind AI Cybersecurity Technical and Research Lead, Google DeepMind
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