Securing AI Pipelines from Development to Production

Securing AI Pipelines from Development to Production

Conf42 via YouTube Direct link

17:17 Core Takeaways and Conclusion

15 of 15

15 of 15

17:17 Core Takeaways and Conclusion

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Classroom Contents

Securing AI Pipelines from Development to Production

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  1. 1 00:00 Introduction and Speaker Background
  2. 2 00:23 The New Battlefield: ML Ops Security Challenges
  3. 3 01:53 Agenda Overview
  4. 4 02:35 Defining the Core Problem
  5. 5 03:52 Hidden Threats in ML Ops
  6. 6 05:03 Introducing Zero Trust
  7. 7 06:21 Implementing Zero Trust in ML Lifecycle
  8. 8 07:04 Stage 1: Securing Data Preparation
  9. 9 08:08 Stage 2: Model Training and Validation
  10. 10 09:32 Stage 3: Deployment and Serving
  11. 11 10:43 Stage 4: Monitoring and Governance
  12. 12 12:46 Real-World Impact and Case Studies
  13. 13 13:57 Actionable Steps to Begin
  14. 14 15:05 Tools and Common Pitfalls
  15. 15 17:17 Core Takeaways and Conclusion

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