It is possible to manage 10 ML models manually. It may be possible to manage 100 models through scripts and alerts. But, managing 1000+ models requires an entirely different approach. The MLOps playbook provides a cohesive approach to bring together the three key elements toward a successful implementation.
Sumit Agarwal
Sr Director Analyst
Sumit Agarwal is a technologist with a practitioner mindset and extensive experience on solutions implementations across data and AI technologies. He has a research focus on Artificial Intelligence, Machine Learning, Advanced Analytics and Data Science. He provides guidance on AI topics including end-to-end solution implementations, architectures, frameworks and best practices related to cloud AI, responsible AI (explainability, privacy, fairness, adversarial robustness), skills development and organization structure, governance, technical strategy and open-source components.
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Monday, 19 September, 2022 / 04:15 PM - 04:45 PM IST
Technical Insights: Develop Your MLOps Playbook to Accelerate Machine Learning Deployment
Tuesday, 20 September, 2022 / 10:30 AM - 11:00 AM IST
Technical Insights: Struggling With Establishing Trust in AI? Reduce Model Bias and Incorporate Explainable AI
The use of predictive models creates trust challenges for enterprises. Model bias and lack of transparency are primary challenges for the trust gap. This session will demystify the approaches to mitigate bias and making the models explainable leveraging organizational people, improved processes and platform enhancements.