Machine learning scientist with domain expertise in chemicals, materials, medical sciences, and environment. A creative at core, passionate about building elegant things and finding elegant solutions. Extensive background in large vision language models, deep learning, computer vision, machine learning using linear and logistic regression, convolutional neural networks, clustering algorithms, support vector machines, graph neural networks, generative adversarial networks and so on, in domains of physics, chemistry, environmental science, biology, pharmaceuticals, chemical engineering, and materials science.
Manager, Data Science Core, Arkansas Integrative Metabolic Research Center.
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University of Arkansas
- Fayetteville
- www.prateekverma.com
Highlights
- Pro
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pvnrt
pvnrt PublicHolds reusable modules/classes and methods/functions for filesystem, image processing, machine learning etc. tasks
Python
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