Trusted and Responsible AI - Explainability, Adversarial Attacks, Bias, and Fairness

Trusted and Responsible AI - Explainability, Adversarial Attacks, Bias, and Fairness

Linux Foundation via YouTube Direct link

Evasion attacks

11 of 15

11 of 15

Evasion attacks

Class Central Classrooms beta

YouTube playlists curated by Class Central.

Classroom Contents

Trusted and Responsible AI - Explainability, Adversarial Attacks, Bias, and Fairness

Automatically move to the next video in the Classroom when playback concludes

  1. 1 OPEN SOURCE SUMMIT
  2. 2 Speaker Profile
  3. 3 Introduction
  4. 4 The Principles of responsible Al
  5. 5 Why XAI is important?
  6. 6 Adversarial Machine Learning Defenses
  7. 7 Adversarial training
  8. 8 Switching models
  9. 9 Generalised models
  10. 10 Poisoning attacks
  11. 11 Evasion attacks
  12. 12 Model stealing
  13. 13 Methods of combating attacks
  14. 14 Fixing biases in Al and machine learning algorithms
  15. 15 Conclusion

Never Stop Learning.

Get personalized course recommendations, track subjects and courses with reminders, and more.

Someone learning on their laptop while sitting on the floor.