Linear Algebra with Machine Learning and Data

Arangala, Crista

Linear Algebra with Machine Learning and Data
  • 出版商: CRC
  • 出版日期: 2023-05-09
  • 售價: $3,530
  • 貴賓價: 9.5 折 $3,354
  • 語言: 英文
  • 頁數: 290
  • 裝訂: Hardcover - also called cloth, retail trade, or trade
  • ISBN: 036745839X
  • ISBN-13: 9780367458393
  • 相關分類: Machine Learning、線性代數 Linear-algebra

    • 下單後立即進貨 (約2~4週)

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商品描述

This book takes a deep dive into several key linear algebra subjects as they apply to data analytics and data mining. The book offers a case study approach where each case will be grounded in a real-world application.

This text is meant to be used for a second course in applications of Linear Algebra to Data Analytics, with a supplemental chapter on Decision Trees and their applications in regression analysis. The text can be considered in two different but overlapping general data analytics categories: clustering and interpolation.

Knowledge of mathematical techniques related to data analytics and exposure to interpretation of results within a data analytics context are particularly valuable for students studying undergraduate mathematics. Each chapter of this text takes the reader through several relevant case studies using real-world data.

All data sets, as well as Python and R syntax, are provided to the reader through links to Github documentation. Following each chapter is a short exercise set in which students are encouraged to use technology to apply their expanding knowledge of linear algebra as it is applied to data analytics.

A basic knowledge of the concepts in a first Linear Algebra course is assumed; however, an overview of key concepts is presented in the Introduction and as needed throughout the text.

商品描述(中文翻譯)

本書深入探討了幾個與數據分析和數據挖掘相關的線性代數主題。該書採用案例研究的方式，每個案例都以真實世界的應用為基礎。

本書旨在用於應用線性代數於數據分析的第二門課程，並附有一個關於決策樹及其在回歸分析中的應用的補充章節。本書可被視為兩個不同但有重疊的一般數據分析類別的一部分：聚類和插值。

對於學習本科數學的學生來說，了解與數據分析相關的數學技巧並在數據分析的背景下解釋結果的能力尤為重要。本書的每一章都通過幾個相關的案例研究使用真實世界的數據引導讀者。

所有數據集以及Python和R的語法都通過鏈接到Github文檔提供給讀者。每章後面都有一個短的練習集，鼓勵學生使用技術將他們對線性代數應用於數據分析的知識擴展。

假設讀者對於第一門線性代數課程中的概念有基本的了解；然而，本書在引言中以及在需要時會對關鍵概念進行概述。

作者簡介

Dr. Crista Arangala is Professor of Mathematics and Chair of the Department of Mathematics and Statistics at Elon University in North Carolina. She has been teaching and researching in a variety of fields including inverse problems, applied partial differential equations, applied linear algebra, mathematical modeling and service learning education. She runs a traveling science museum with her Elon University students in Kerala, India. Dr. Arangala was chosen to be a Fulbright Scholar in 2014 as a visiting lecturer at the University of Colombo where she continued her projects in inquiry learning in Linear Algebra and began working with a modeling team focusing on Dengue fever research. Dr. Arangala has published several textbooks that implore inquiry learning techniques including Exploring Linear Algebra: Labs and Projects with MATLAB(R) and Mathematical Modeling: Branching Beyond Calculus.

作者簡介(中文翻譯)

Dr. Crista Arangala是北卡羅來納州Elon大學數學和統計學系的教授和系主任。她在多個領域進行教學和研究，包括反問題、應用偏微分方程、應用線性代數、數學建模和服務學習教育。她與Elon大學的學生在印度喀拉拉邦運營一個流動科學博物館。2014年，Arangala博士被選為富布萊特學者，擔任斯里蘭卡科倫坡大學的訪問講師，繼續進行線性代數的探究學習項目，並開始與一個關注登革熱研究的建模團隊合作。Arangala博士出版了幾本採用探究學習技術的教科書，包括《探索線性代數：使用MATLAB(R)的實驗和項目》和《數學建模：超越微積分的分支》。

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