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TECHNICAL | Taming the Drift: Sustaining Model Performance in a Dynamic World
11 Jun 2025
Masterclass Programme
Masterclass Programme
What You’ll Learn:
- Why model drift is a critical challenge in dynamic, real-world AI deployments
- How to detect and mitigate model degradation using real-time monitoring and retraining pipelines
- Proven strategies for maintaining model accuracy, including adaptive systems and feedback loops
- Insights into building scalable infrastructure to support continuous model performance
- Real-world case studies from organizations that have tackled drift successfully
- How to turn operational setbacks into opportunities for innovation and agility
- What it takes to future-proof your AI systems in fast-changing environments
Why This Matters:
As industries evolve, data shifts and even the best AI models can start to fail. In this 50-minute masterclass, you’ll learn how to stay ahead of model drift with proactive strategies that ensure consistent performance over time. From automated retraining to adaptive monitoring systems, we’ll walk through the practical techniques and tools that help data teams stay agile in high-stakes environments. You’ll leave with actionable ideas, infrastructure insights, and a clearer understanding of how to build AI systems that don’t just launch—but last.
Who Should Attend:
- ML Engineers & Data Scientists
- AI Infrastructure Leads & MLOps Professionals
- Technical Decision Makers & AI Strategists
- Innovation & R&D Leaders
Pass Type
VIP All Access Pass,Delegate Pass,Start-up & Investor Pass,Academic Pass,Press Pass
Content Focus
Technical
Session Type
Masterclass
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