Krishna Gade
where else to find them
linkedin:krishnagade
what they talk about
all 4 in the filters
where they keep going back
- TWIMLcon: AI Platforms2 editions2019–2021
on a stage with
- Krishna Gade Fiddleronce
- Rob Harrellonce
who talks about the same things
- Guangya Liu5 talks
- Emeli Dral8 talks
- Sameer Paradkar3 talks
- Wojtek Kuberski7 talks
- Alois Reitbauer17 talks
- Harry Kimpel9 talks
| title | conference | date |
|---|---|---|
| Model Performance Monitoring - A Practitioner's Perspective | AI @Scale 2022 | 2022-09-28 |
Claims a deployable Model Performance Management platform that continuously detects concept, data, label and feature drift, attributes degradations with a… | ||
| Minimize Risks and Accelerate MLOps with Model Performance Monitoring and Explainability | Data @Scale Spring 2022 | 2022-05-18 |
Fiddler ships a model performance management system that compares production and training distributions using Jensen‑Shannon divergence to flag prediction… | ||
| Explainable Monitoring for Successful AI Deployments | TWIMLcon: AI Platforms 2021 | 2021-01-19 |
A monitoring system called Fiddler injects explainability into production models by computing drift with Jensen-Shannon divergence and attributing it via a… | ||
| Why and How to Build Explainability into your ML Workflow | TWIMLcon: AI Platforms 2019 | 2019-10-01 |
Companies report nearly half lack trust in AI and regulators invoke Article 22 (GDPR), so explainability becomes a compliance and risk tool. Practical methods… | ||
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