Emeli Dral
where else to find them
what they talk about
all 4 in the filters
where they keep going back
- PyData London2 editions2024–2025
- PyData Global2 editions2022–2023
on a stage with
never shared a talk
who talks about the same things
- Wojtek Kuberski7 talks
- Patrick Deziel4 talks
- Ben Lorica15 talks
- Tobias Sterbak4 talks
- Alejandro Saucedo33 talks
- Bas Geerdink13 talks
| title | conference | date |
|---|---|---|
| AI agents testing How to evaluate the unpredictable | PyData London 2025 | 2025-06-06 |
Projects prioritize unit, integration and end‑to‑end tests wired into CI/CD. Prompts and tools are treated as functions; validate formats with JSON schema… | ||
| How continuous testing keeps your LLM on track | PyData London 2024 | 2024-06-14 |
Argues that continuous testing catches regressions and drift by combining an evolving golden dataset, runtime logging, and scheduled checks; shows practical… | ||
| More like this: monitoring recommender systems in production | PyData Global 2023 | 2023-12-06 |
Practical checklist: measure a revenue KPI first, add real‑time proxy metrics (clicks, views, conversion) and batch compute offline metrics like Precision@K… | ||
| Why we do ML model retraining wrong, and how to do better | PyData Global 2022 | 2022-12-01 |
Machine learning models degrade over time so the concrete proposal is: monitor model quality and error distributions, run per-step data checks inside… | ||
| Detecting drift: how to evaluate and explore data drift in machine learning systems | PyCon DE & PyData Berlin 2022 | 2022-04-11 |
Uses drift as an early proxy for performance when ground truth is unavailable and gives concrete methods: choose parametric tests (t/z) for sensitive detection… | ||
| nothing matches | ||