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DTSTART:20210817T170000Z
DTEND:20210817T181500Z
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SUMMARY:Big Data Peer Group | Operationalizing & Scaling Trusted AI
DESCRIPTION:Operationalizing & Scaling Trusted AI \n\nWith Swami Chandrasekaran\n\nHead of Solution Architecture\, KPMG US\n\n\n\nOverview:\n\nTraining AI including machine learning models has become easier than ever before\, but to operationalize those models and make them production-ready is a totally different ballgame. In this session\, you will learn about key techniques\, challenges\, and considerations when building AI models that are responsible\, secure\, and production-ready. Topics include\, but are not limited to\, model lifecycle\, models serving\, MLOps\, bias and drift detection\, explainability of models\, model observability and monitoring\, and model and data governance etc. You will also learn about various tools\, platform & libraries that are available to consider.\n\n\n\nBio:\n\nSwami drives technology and architecture for complex digital solutions. He has over 20 years of technology and engineering experience in delivering outcomes using "Process\, AI\, Data and Automation" in a broad range of industries. In his current role\, he works with clients to architect solutions across several industries that combine AI including advanced analytics\, IoT\, AR/VR\, and automation technologies deployed on multi-clouds. He has built middleware products\, cloud-first AI platforms as well as working with clients in 20+ countries to deploy them successfully.
X-ALT-DESC;FMTTYPE=text/html:Operationalizing &amp\; Scaling Trusted AI&nbsp\;<br />\nWith Swami Chandrasekaran<br />\nHead of Solution Architecture\, KPMG US<br />\n<br />\nOverview:<br />\nTraining AI including machine learning models has become easier than ever before\, but to operationalize those models and make them production-ready is a totally different ballgame. In this session\, you will learn about key techniques\, challenges\, and considerations when building AI models that are responsible\, secure\, and production-ready.&nbsp\;Topics include\, but are not limited to\, model lifecycle\, models serving\, MLOps\, bias and drift detection\, explainability of models\, model observability and monitoring\, and model and data governance etc. You will also learn about various tools\, platform &amp\; libraries that are available to consider.<br />\n<br />\nBio:<br />\nSwami drives technology and architecture for complex digital solutions. He has over 20 years of technology and engineering experience in delivering outcomes using &ldquo\;Process\, AI\, Data and Automation&rdquo\; in a broad range of industries. In his current role\, he works with clients to architect solutions across several industries that combine AI including advanced analytics\, IoT\, AR/VR\, and automation technologies deployed on multi-clouds. He has built middleware products\, cloud-first AI platforms as well as working with clients in 20+ countries to deploy them successfully.&nbsp\;
LOCATION:Virtual - Zoom
UID:e.9470.2140
SEQUENCE:3
DTSTAMP:20260428T124222Z
URL:https://business.nmtechcouncil.org/events/details/big-data-peer-group-operationalizing-scaling-trusted-ai-2140
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