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: 2024-10-04
  • 售價: $2,170
  • 貴賓價: 9.5 折 $2,062
  • 語言: 英文
  • 頁數: 575
  • 裝訂: Quality Paper - also called trade paper
  • ISBN: 3031133412
  • ISBN-13: 9783031133411
  • 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)

這本教科書為學生提供了分析複雜數據所需的工具，使用數據科學、機器學習和人工智慧的方法。作者不僅介紹了這些方法，還提供了使用程式語言 R 的應用，R 是分析數據的黃金標準。作者涵蓋了數據科學的三個主要組成部分：計算機科學、數學與統計以及領域知識。這本書將方法和 R 的實作並排呈現，讓學習概念能立即實際應用。此外，這也以自然的方式教授計算思維。書中包含練習題、案例研究、問答和範例。

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。他領導預測社會與數據分析實驗室，該實驗室專注於深度學習和自然語言處理的創新研究。實驗室開發並應用高維方法於機器學習、統計學和人工智慧，這些方法可用於從生物學、醫學、社交媒體、社會科學、市場行銷或商業等領域的數據中提取知識。

Salissou Moutari 是英國貴族大學的高級講師及數學科學研究中心（MSRC）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，以及這些方法在交通、運輸和分配系統、生產規劃和工業過程中的應用。

Matthias Dehmer 是奧地利 UMIT 的教授，同時在瑞士布里格的瑞士應用科技大學擔任職位。他的研究興趣包括複雜網絡、複雜性、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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