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4. Deep Learning in Embedded Electronics for Short-Term Storm Forecasting with Max von Wolff

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Manage episode 313356328 series 3267799
Content provided by Brendon Matusch, Anish Singhani, Brendon Matusch, and Anish Singhani. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Brendon Matusch, Anish Singhani, Brendon Matusch, and Anish Singhani or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.
Brendon and Anish interview Max von Wolff, a student from Mayen, Germany, about his research on short-term predictions of storm movement using deep learning with a network of distributed weather observation devices. We discuss the advantages and difficulties of processing data collected with embedded devices in the field, the use of machine learning methods such as autoencoders for processing this data, and Max's plans to scale up his research! Please send comments to shatteredgradients@gmail.com.
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7 episodes

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Archived series ("Inactive feed" status)

When? This feed was archived on October 16, 2024 09:09 (26d ago). Last successful fetch was on December 09, 2021 19:25 (3y ago)

Why? Inactive feed status. Our servers were unable to retrieve a valid podcast feed for a sustained period.

What now? You might be able to find a more up-to-date version using the search function. This series will no longer be checked for updates. If you believe this to be in error, please check if the publisher's feed link below is valid and contact support to request the feed be restored or if you have any other concerns about this.

Manage episode 313356328 series 3267799
Content provided by Brendon Matusch, Anish Singhani, Brendon Matusch, and Anish Singhani. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Brendon Matusch, Anish Singhani, Brendon Matusch, and Anish Singhani or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.
Brendon and Anish interview Max von Wolff, a student from Mayen, Germany, about his research on short-term predictions of storm movement using deep learning with a network of distributed weather observation devices. We discuss the advantages and difficulties of processing data collected with embedded devices in the field, the use of machine learning methods such as autoencoders for processing this data, and Max's plans to scale up his research! Please send comments to shatteredgradients@gmail.com.
  continue reading

7 episodes

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