Linear Algebra for Data Science with Python
暫譯: 使用 Python 的數據科學線性代數
Shea, John M.
- 出版商: CRC
- 出版日期: 2025-10-31
- 售價: $4,020
- 貴賓價: 9.5 折 $3,819
- 語言: 英文
- 頁數: 248
- 裝訂: Hardcover - also called cloth, retail trade, or trade
- ISBN: 1032659165
- ISBN-13: 9781032659169
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相關分類:
Python、線性代數 Linear-algebra
海外代購書籍(需單獨結帳)
商品描述
Linear Algebra for Data Science with Python provides an introduction to vectors and matrices within the context of data science. This book starts from the fundamentals of vectors and how vectors are used to model data, builds up to matrices and their operations, and then considers applications of matrices and vectors to data fitting, transforming time-series data into the frequency domain, and dimensionality reduction. This book uses a computational-first approach: the reader will learn how to use Python and the associated data-science libraries to work with and visualize vectors and matrices and their operations, as well as to import data to apply these techniques. Readers learn the basics of performing vector and matrix operations by hand but are also shown how to use several different Python libraries for performing these operations.
Key Features:
- Teaches the most important concepts and techniques for working with multi-dimensional data using vectors and matrices.
- Introduces readers to the some of the most important Python libraries for working with data, including NumPy and and PyTorch.
- Examples using real data and engineering applications show the utility of the techniques covered in this book.
- Includes many color visualizations to illustrate mathematical operations involving vectors and matrices.
- Offers an accompanying website that provides a unique set of online, interactive tools to help the reader learn the material.
商品描述(中文翻譯)
《線性代數與 Python 的資料科學》提供了在資料科學背景下對向量和矩陣的介紹。本書從向量的基本概念開始，探討向量如何用來建模資料，然後逐步深入到矩陣及其運算，並考慮矩陣和向量在資料擬合、將時間序列資料轉換到頻域以及降維中的應用。本書採用計算優先的方法：讀者將學習如何使用 Python 及相關的資料科學庫來處理和視覺化向量和矩陣及其運算，並導入資料以應用這些技術。讀者將學習手動執行向量和矩陣運算的基本知識，同時也會展示如何使用幾個不同的 Python 庫來執行這些運算。
主要特色：
- 教授使用向量和矩陣處理多維資料的最重要概念和技術。
- 介紹一些最重要的 Python 庫以處理資料，包括 NumPy 和 PyTorch。
- 使用真實資料和工程應用的範例展示本書所涵蓋技術的實用性。
- 包含許多彩色視覺化圖示，以說明涉及向量和矩陣的數學運算。
- 提供一個附屬網站，提供一套獨特的在線互動工具，幫助讀者學習材料。
作者簡介
John M. Shea, PhD is a Professor in the Department of Electrical and Computer Engineering at the University of Florida, where he has taught classes on stochastic methods, data science, and wireless communications for over 25 years. He earned his PhD in Electrical Engineering from Clemson University in 1998 and later received the Outstanding Young Alumni award from the Clemson College of Engineering and Science. Dr. Shea was co-leader of Team GatorWings, which won the Defense Advanced Research Project Agency's (DARPA's) Spectrum Collaboration Challenge (DARPA's fifth Grand Challenge) in 2019; he received the Lifetime Achievement Award for Technical Achievement from the IEEE Military Communications Conference (MILCOM) and is a two-time winner of the Ellersick Award from the IEEE Communications Society for the Best Paper in the Unclassified Program of MILCOM.
作者簡介(中文翻譯)
約翰·M·謝 (John M. Shea) 博士是佛羅里達大學電機與計算機工程系的教授，已教授隨機方法、數據科學和無線通信等課程超過25年。他於1998年在克萊姆森大學獲得電機工程博士學位，並隨後獲得克萊姆森工程與科學學院的傑出青年校友獎。謝博士是GatorWings團隊的共同領導者，該團隊在2019年贏得了國防高級研究計劃局（DARPA）的頻譜協作挑戰（DARPA的第五屆大挑戰）；他獲得了IEEE軍事通信會議（MILCOM）頒發的技術成就終身成就獎，並兩次獲得IEEE通信學會的Ellersick獎，以表彰在MILCOM的非分類計劃中最佳論文。
