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Automate caption creation and search for images at enterprise scale using generative AI and Amazon Kendra

AWS Machine Learning

It has applications in areas where data is multi-modal such as ecommerce, where data contains text in the form of metadata as well as images, or in healthcare, where data could contain MRIs or CT scans along with doctor’s notes and diagnoses, to name a few use cases.

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Federated learning on AWS using FedML, Amazon EKS, and Amazon SageMaker

AWS Machine Learning

However, the sharing of raw, non-sanitized sensitive information across different locations poses significant security and privacy risks, especially in regulated industries such as healthcare. Limiting the available data sources to protect privacy negatively affects result accuracy and, ultimately, the quality of patient care.

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Promote pipelines in a multi-environment setup using Amazon SageMaker Model Registry, HashiCorp Terraform, GitHub, and Jenkins CI/CD

AWS Machine Learning

She is passionate about solving customer pain points processing big data and providing long-term scalable solutions. Prior to this role, she developed products in internet, telecom, and automotive domains, and has been an AWS customer. She holds a master’s degree in Data Science from the University of California, Riverside.

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