| 書目名稱 | Fundamentals of Supervised Machine Learning | | 副標(biāo)題 | With Applications in | | 編輯 | Giovanni Cerulli | | 視頻video | http://file.papertrans.cn/351/350588/350588.mp4 | | 概述 | Presents the fundamental notions of supervised machine learning.Provides a balance between the theory and applications of machine learning using Python, R, and Stata.Fosters an understanding and aware | | 叢書名稱 | Statistics and Computing | | 圖書封面 |  | | 描述 | .This book presents the fundamental theoretical notions of supervised machine learning along with a wide range of applications using Python, R, and Stata. It provides a balance between theory and applications and fosters an understanding and awareness of the availability of machine learning methods over different software platforms..After introducing the machine learning basics, the focus turns to a broad spectrum of topics: model selection and regularization, discriminant analysis, nearest neighbors, support vector machines, tree modeling, artificial neural networks, deep learning, and sentiment analysis. Each chapter is self-contained and comprises an initial theoretical part, where the basics of the methodologies are explained, followed by an applicative part, where the methods are applied to real-world datasets. Numerous examples are included and, for ease of reproducibility, the Python, R, and Stata codes used in the text, along with the related datasets, are available online..The intended audience is PhD students, researchers and practitioners from various disciplines, including economics and other social sciences, medicine and epidemiology, who have a good understanding of b | | 出版日期 | Textbook 2023 | | 關(guān)鍵詞 | Supervised Machine Learning; Machine Learning; Statistical Learning; Python; Stata; R Software; Machine Le | | 版次 | 1 | | doi | https://doi.org/10.1007/978-3-031-41337-7 | | isbn_softcover | 978-3-031-41339-1 | | isbn_ebook | 978-3-031-41337-7Series ISSN 1431-8784 Series E-ISSN 2197-1706 | | issn_series | 1431-8784 | | copyright | The Editor(s) (if applicable) and The Author(s), under exclusive licence to Springer Nature Switzerl |
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