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key challenges: data drift
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Classroom Contents
The Next Frontier - Observability in ML Systems
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- 1 intro
- 2 preamble
- 3 who am i?
- 4 what is model observability?
- 5 how is model observability different from model monitoring?
- 6 why is model observability important?
- 7 how ml observability helps
- 8 key components of ml observability
- 9 key challenges: data drift
- 10 key challenges: performance degradation
- 11 key challenges: data quality
- 12 model observability challenges in llms
- 13 evaluation techniques for llms
- 14 challenges in computer vision
- 15 components to address challenges in computer vision
- 16 monitoring techniques in ml observability
- 17 explainability techniques in standard ml systems
- 18 explainability techniques in llms
- 19 explainability techniques in cv
- 20 future trends in model observability
- 21 thanks for attention
