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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
İçerik Brendon Matusch, Anish Singhani, Brendon Matusch, and Anish Singhani tarafından sağlanmıştır. Bölümler, grafikler ve podcast açıklamaları dahil tüm podcast içeriği doğrudan Brendon Matusch, Anish Singhani, Brendon Matusch, and Anish Singhani veya podcast platform ortağı tarafından yüklenir ve sağlanır. Birinin telif hakkıyla korunan çalışmanızı izniniz olmadan kullandığını düşünüyorsanız burada https://tr.player.fm/legal özetlenen süreci takip edebilirsiniz.
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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