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The focus of this book is on the application of machine learning techniques to enhance the efficiency of costly fundamental science experiments. It delves into innovative methods that leverage data analysis and predictive modeling to streamline research processes, ultimately aiming to reduce costs and improve outcomes in scientific inquiry. Through various case studies and examples, the book illustrates the transformative potential of integrating advanced computational tools in experimental science.
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Machine Learning at the Belle II Experiment, Thomas Keck
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- 2019
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