| 書(shū)目名稱(chēng) | Statistical Machine Learning for Engineering with Applications | | 編輯 | Jürgen Franke,Anita Sch?bel | | 視頻video | http://file.papertrans.cn/877/876471/876471.mp4 | | 概述 | Serves as a n introduction to statistical machine learning for students, requiring only a basic training in statistics.Enables engineers and scientists to understand the potential and pitfalls of mach | | 叢書(shū)名稱(chēng) | Lecture Notes in Statistics | | 圖書(shū)封面 |  | | 描述 | .This book offers a leisurely introduction to the concepts and methods of machine learning. Readers will learn about classification trees, Bayesian learning, neural networks and deep learning, the design of experiments, and related methods. For ease of reading, technical details are avoided as far as possible, and there is a particular emphasis on applicability, interpretation, reliability and limitations of the data-analytic methods in practice. To cover the common availability and types of data in engineering, training sets consisting of independent as well as time series data are considered. To cope with the scarceness of data in industrial problems, augmentation of training sets by additional artificial data, generated from physical models, as well as the combination of machine learning and expert knowledge of engineers are discussed...The methodological exposition is accompanied by several detailed case studies based on industrial projects covering a broad range of engineering applications from vehicle manufacturing, process engineering and design of materials to optimization of production processes based on image analysis...The focus is on fundamental ideas, applicability and | | 出版日期 | Textbook 2024 | | 關(guān)鍵詞 | Linear Regression; Crossvalidation; Bayesian Linear Regression; Local Averaging; Neural Networks; Dimensi | | 版次 | 1 | | doi | https://doi.org/10.1007/978-3-031-66253-9 | | isbn_softcover | 978-3-031-66252-2 | | isbn_ebook | 978-3-031-66253-9Series ISSN 0930-0325 Series E-ISSN 2197-7186 | | issn_series | 0930-0325 | | copyright | The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl |
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