Elements of Data Science, Machine Learning, and Artificial Intelligence Using R

Emmert-Streib, Frank, Moutari, Salissou, Dehmer, Matthias

Elements of Data Science, Machine Learning, and Artificial Intelligence Using R
  • 出版商: Springer
  • 出版日期: 2023-10-04
  • 售價: $2,780
  • 貴賓價: 9.5 折 $2,641
  • 語言: 英文
  • 頁數: 575
  • 裝訂: Hardcover - also called cloth, retail trade, or trade
  • ISBN: 3031133382
  • ISBN-13: 9783031133381
  • 相關分類: 人工智慧、Machine Learning、Data Science

    • 海外代購書籍(需單獨結帳)

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商品描述

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.

商品描述(中文翻譯)

這本教科書提供學生使用資料科學、機器學習和人工智慧方法來分析複雜資料的工具。作者們不僅介紹方法，還使用R程式語言進行應用，R是分析資料的黃金標準。作者們涵蓋了資料科學的三個主要組成部分：計算機科學、數學和統計學，以及領域知識。這本書將方法和R的實現並列呈現，使學習概念能夠立即實際應用。此外，這本書以自然的方式教授計算思維。書中包含練習題、案例研究、問答和例子。

作者簡介

Frank Emmert-Streib is Professor of Data Science at Tampere University (Finland). He leads the Predictive Society and Data Analytics Lab, which pursues innovative research in deep learning and natural language processing. The Lab develops and applies high-dimensional methods in machine learning, statistics, and artificial intelligence that can be used to extract knowledge from data in the fields of biology, medicine, social media, social sciences, marketing, or business.

Salissou Moutari is Senior Lecturer at Queen's University Belfast (UK) and Interim Director of Research of the Mathematical Science Research Centre (MSRC). His research interests include mathematical modelling, optimization, machine learning and data science, and the applications of these methods to problems from traffic, transportation and distribution systems, production planning and industrial processes.

Matthias Dehmer is Professor at UMIT (Austria) and also has a position at Swiss Distance University of Applied Sciences, Brig, Switzerland. His research interests are in complex networks, complexity, data science, machine learning, big data analytics, and information theory. In particular, he is working on machine learning based methods to analyse high-dimensional data.


作者簡介(中文翻譯)

Frank Emmert-Streib是芬蘭坦佩雷大學的數據科學教授。他領導著預測社會和數據分析實驗室，該實驗室致力於深度學習和自然語言處理的創新研究。該實驗室開發並應用機器學習、統計和人工智能中的高維方法，可用於從生物學、醫學、社交媒體、社會科學、市場營銷或商業領域的數據中提取知識。

Salissou Moutari是英國貝爾法斯特女王大學的高級講師，也是數學科學研究中心（MSRC）的臨時研究主任。他的研究興趣包括數學建模、優化、機器學習和數據科學，以及將這些方法應用於交通、運輸和分配系統、生產計劃和工業過程等問題。

Matthias Dehmer是奧地利UMIT大學的教授，同時還在瑞士應用科學遠程大學布里格分校擔任職位。他的研究興趣包括複雜網絡、復雜性、數據科學、機器學習、大數據分析和信息理論。特別是，他正在研究基於機器學習的方法來分析高維數據。

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