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The theory of data assimilation and machine learning is introduced in an accessible and pedagogical manner, with a focus on the underlying statistical physics. This modern and cross-disciplinary book is suitable for undergraduate and graduate students from science and engineering without specialized experience of statistical physics.

Produktbeschreibung
The theory of data assimilation and machine learning is introduced in an accessible and pedagogical manner, with a focus on the underlying statistical physics. This modern and cross-disciplinary book is suitable for undergraduate and graduate students from science and engineering without specialized experience of statistical physics.
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Autorenporträt
Henry D. I. Abarbanel has worked in several fields of physics including high energy physics, nonlinear dynamics, and data assimilation in neurobiology. He is the author of two previous books: Analysis of Observed Chaotic Data (1996) and Predicting the Future: Completing Models of Observed Complex Systems (2013). He is a Distinguished Professor of Physics at University of California, San Diego (UCSD) and a Distinguished Research Physicist at UCSD's Scripps Institution of Oceanography.