Exploring Se4ai Model Quality
Exploring Se4ai Model Quality reveals several interesting facts.
- Beyond data and
- Sixth lecture of the Carnegie Mellon course "17-445/645 Software Engineering for AI-Enabled Systems", Summer 2020 Discusses ...
- Discussing security principles in general and ML-specific attacks (poisoning attacks, evasion attacks) and counter strategies both ...
- Discussing safety of systems with an ML component, classic safety strategies (requirements, hazard analysis, system design), ...
- Short lecture after Molham's invited talk, catching up on data programming with Snorkel and briefly discussing challenges of ...
In-Depth Information on Se4ai Model Quality
4th lecture of the Carnegie Mellon course "17-445/645 Software Engineering for AI-Enabled Systems", Summer 2020 Discusses ... About various kinds of data ... Summer 2020 Catches up on some more About the ultimate heldout test data: production data. Covers measuring
Fairness is a challenge, but we can actually do many things: Measures of fairness and how they correspond to different goals and ...
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