Machine Learning in Astronomy (IAU S368): Possibilities and Pitfalls - Proceedings of the International Astronomical Union Symposia and Colloquia - Ashish Mahabal-Jess Mciver-Christopher Fluke - Books - Cambridge University Press - 9781009345194 - October 16, 2025
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Ashish Mahabal-Jess Mciver-Christopher Fluke
Machine Learning in Astronomy (IAU S368): Possibilities and Pitfalls - Proceedings of the International Astronomical Union Symposia and Colloquia

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IAU S368 addresses graduate students and professional astronomers who wish to leverage machine learning to unlock the potential of modern data-rich surveys and deep images, as well as archival data. Researchers at the frontiers share best practices in applied machine learning that are relevant to astronomy and other data-rich fields.

Media Books     Hardcover Book   (Book with hard spine and cover)
Released October 16, 2025
ISBN13 9781009345194
Publishers Cambridge University Press
Pages 200
Dimensions 254 × 178 × 11 mm   ·   398 g
Editor Fluke, Christopher (Swinburne University of Technology, Victoria)
Editor Mahabal, Ashish (California Institute of Technology)
Editor McIver, Jess (University of British Columbia, Vancouver)

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