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12:26 Conclusion and Q&A
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Classroom Contents
Embedding Security and Ethics into the ML Pipeline
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- 1 00:00 Introduction and Speaker Background
- 2 00:15 Challenges in AI and Machine Learning
- 3 00:42 Case Study: Retail Company AI Failure
- 4 01:58 Need for Strong DevOps in AI
- 5 02:09 Fast Deployment Issues
- 6 03:25 AI Native DevSecOps Framework
- 7 04:10 Secure Data Injection
- 8 05:14 Privacy Preserving Training
- 9 06:38 Security Testing in ML Pipelines
- 10 07:27 Protecting Inference Endpoints
- 11 08:29 Governance and Ethical AI
- 12 10:37 Real-World Success Stories
- 13 11:27 Strategies for Organizations
- 14 12:03 Key Takeaways
- 15 12:26 Conclusion and Q&A
