書目名稱 | Elements of Data Science, Machine Learning, and Artificial Intelligence Using R | 編輯 | Frank Emmert-Streib,Salissou Moutari,Matthias Dehm | 視頻video | http://file.papertrans.cn/308/307581/307581.mp4 | 概述 | Provides students with tools they need to analyze complex data using methods from data science.Presents the tools students need to analyze data using the R programming language.Includes a full suite o | 圖書封面 |  | 描述 | The textbook provides students with tools they need to analyze complex data using methods from data science, machine learning and artificial intelligence. The authors include both the presentation of methods along with applications using the programming language R, which is the gold standard for analyzing data. The authors cover all three main components of data science: computer science; mathematics and statistics; and domain knowledge. The book presents methods and implementations in R side-by-side, allowing the immediate practical application of the learning concepts. Furthermore, this teaches computational thinking in a natural way. The book includes exercises, case studies, Q&A and examples.. | 出版日期 | Textbook 2023 | 關(guān)鍵詞 | Data science; Algorithms; data driven sciences; Learning from data; Prediction models; Bayesian analysis | 版次 | 1 | doi | https://doi.org/10.1007/978-3-031-13339-8 | isbn_softcover | 978-3-031-13341-1 | isbn_ebook | 978-3-031-13339-8 | copyright | The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl |
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