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Meet the Fellow: Jonathan Colner

NYU Center for Data Science

He is particularly interested in using object detection and large language models to extract and clean data from messy local government administrative sources, such as city council meeting minutes and municipal codes. I’m excited to join NYU CDS and work at the intersection of data science and local politics,” said Colner.

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Tableau: 9 years a Leader in Gartner Magic Quadrant for Analytics and Business Intelligence Platforms

Tableau

We also reached some incredible milestones with Tableau Prep, our easy-to-use, visual, self-service data prep product. In 2020, we added the ability to write to external databases so you can use clean data anywhere. Tableau Prep can now be used across more use cases and directly in the browser.

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Identifying defense coverage schemes in NFL’s Next Gen Stats

AWS Machine Learning Blog

Advances in neural information processing systems 30 (2017). He has been with the Next Gen Stats team for the last seven years helping to build out the platform from streaming the raw data, building out microservices to process the data, to building API’s that exposes the processed data. Attention is all you need.”

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Create high-quality datasets with Amazon SageMaker Ground Truth and FiftyOne

AWS Machine Learning Blog

For our example use case, we work with the Fashion200K dataset , released at ICCV 2017. Solution overview Ground Truth is a fully self-served and managed data labeling service that empowers data scientists, machine learning (ML) engineers, and researchers to build high-quality datasets.

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Tableau: 9 years a Leader in Gartner Magic Quadrant for Analytics and Business Intelligence Platforms

Tableau

We also reached some incredible milestones with Tableau Prep, our easy-to-use, visual, self-service data prep product. In 2020, we added the ability to write to external databases so you can use clean data anywhere. Tableau Prep can now be used across more use cases and directly in the browser.

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