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Deploying Machine Learning Models at Scale in Cloud

Posted Apr 14
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SPEAKER
Vishnu Prathish
Vishnu Prathish
Vishnu Prathish
Director Of Engineering, AI Products @ Innovyze

With 10 years in building production grade data-first software at BBM & HP Labs, I started building Emagin's AI platform about three years ago with the goal of optimizing operations for the water industry. At Innovyze post-acquisition, we are part of the org building world leading water infrastructure data analytics product.

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With 10 years in building production grade data-first software at BBM & HP Labs, I started building Emagin's AI platform about three years ago with the goal of optimizing operations for the water industry. At Innovyze post-acquisition, we are part of the org building world leading water infrastructure data analytics product.

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SUMMARY

The way Data Science is done is changing. Notebook sharing and collaboration were messy and there was minimal visibility or QA into the model deployment process. Vishnu will talk about building an ops platform that deploys hundreds of models at-scale every month. A platform that supports typical features of MLOps (CI/CD, Separated QA, Dev and PROD environment, experiments tracking, Isolated retraining, model monitoring in real-time, Automatic Retraining with live data) and ensures quality and observability without compromising the collaborative nature of data science. 

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