In this webinar, Principal Product Manager Paul Bridi discusses the importance of data-centricity in machine learning operations (MLOps) and how Seldon Core 2 supports this approach. He emphasizes the need for monitoring model reliability, managing resources, and understanding model performance in complex AI applications.
About
Learnings
- The deployment of an income classifier model within a Kubernetes cluster
- How to utilize tools like Prometheus and Grafana for metrics visualization
- The orchestration of pipelines
- The role of microservices
- The significance of data categorization in enhancing model performance
Paul Bridi
Paul Bridi is the Lead Product Manager at Seldon, where he drives the strategy and delivery of AI and MLOps solutions for enterprise customers. With a strong background in product management, AI systems, and operational strategy, Paul has led high-impact projects across sectors. His career spans roles in AI product leadership, data-driven strategy, and software development, underpinned by hands-on experience in analytics, optimization, and technical team management. Paul’s work consistently bridges technical innovation with business value, ensuring AI solutions are robust, scalable, and impactful.
Complex, real-time use cases is what we do best
Talk with a expert to explore how Seldon can support more streamlined deployments for real-time, complex projects like fraud detection, personalization, and so much more.
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