Samantha Edds

Predicting Natural Disasters- Testing the Boundaries of Computer Vision

How well can a computer vision model trained only on point-of-view photos predict on aerial ones? Are some types and aspects of natural disasters easier to predict than others? Sam will speak about this, as well as the applicability and limitations of this kind of work to help us in the real world.

Sam Edds is a passionate leader with a successful track record in using statistics and data modeling to help organizations uncover insights and tell a story to grow their business. Her unique background spanning corporation, start-up, and non-profit settings has shown me the importance of supporting the people, products, and places that make up a community. As a Statistician with roots in International Studies and Development, she firmly believes in harnessing the power of big data to improve the livelihood of all through making more informed, data-driven decisions. While there is more analysis than ever before in the world, something endlessly important to business success, and which remains her focus, is using big data to tell a story and a vision all can grasp. She loves designing and building models to solve problems, and thrives on using her analysis to create a story that all clients (data focused or otherwise) can understand.

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