Foundations of Data Science with Python
Shea, John M.
- 出版商: CRC
- 出版日期: 2024-02-22
- 售價: $7,960
- 貴賓價: 9.5 折 $7,562
- 語言: 英文
- 頁數: 496
- 裝訂: Hardcover - also called cloth, retail trade, or trade
- ISBN: 1032346744
- ISBN-13: 9781032346748
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相關分類:
Python、程式語言、Data Science
海外代購書籍(需單獨結帳)
相關主題
商品描述
Foundations of Data Science with Python introduces readers to the fundamentals of data science, including data manipulation and visualization, probability, statistics, and dimensionality reduction. This book is targeted toward engineers and scientists, but it should be readily understandable to anyone who knows basic calculus and the essentials of computer programming. It uses a computational-first approach to data science: the reader will learn how to use Python and the associated data-science libraries to visualize, transform, and model data, as well as how to conduct statistical tests using real data sets. Rather than relying on obscure formulas that only apply to very specific statistical tests, this book teaches readers how to perform statistical tests via resampling; this is a simple and general approach to conducting statistical tests using simulations that draw samples from the data being analyzed. The statistical techniques and tools are explained and demonstrated using a diverse collection of data sets to conduct statistical tests related to contemporary topics, from the effects of socioeconomic factors on the spread of the COVID-19 virus to the impact of state laws on firearms mortality.
This book can be used as an undergraduate textbook for an Introduction to Data Science course or to provide a more contemporary approach in courses like Engineering Statistics. However, it is also intended to be accessible to practicing engineers and scientists who need to gain foundational knowledge of data science.
Key Features:
- Applies a modern, computational approach to working with data
- Uses real data sets to conduct statistical tests that address a diverse set of contemporary issues
- Teaches the fundamentals of some of the most important tools in the Python data-science stack
- Provides a basic, but rigorous, introduction to Probability and its application to Statistics
- 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)
《Python 數據科學基礎》向讀者介紹數據科學的基本概念,包括數據操作與視覺化、機率、統計和降維。本書的目標讀者為工程師和科學家,但對於具備基本微積分和計算機程式設計基礎的人來說,內容應該也能輕易理解。本書採用以計算為主的數據科學方法:讀者將學習如何使用 Python 及相關的數據科學庫來視覺化、轉換和建模數據,以及如何使用真實數據集進行統計檢定。本書不依賴於僅適用於特定統計檢定的晦澀公式,而是教導讀者如何透過重抽樣來執行統計檢定;這是一種簡單且通用的進行統計檢定的方法,使用從所分析數據中抽取樣本的模擬。統計技術和工具將透過多樣的數據集進行解釋和示範,以進行與當代主題相關的統計檢定,從社會經濟因素對 COVID-19 病毒擴散的影響到州法律對槍支死亡率的影響。
本書可用作本科生的數據科學入門課程教材,或在工程統計等課程中提供更具當代性的教學方法。然而,它也旨在讓需要獲得數據科學基礎知識的在職工程師和科學家能夠輕鬆理解。
主要特色:
- 應用現代計算方法處理數據
- 使用真實數據集進行統計檢定,針對多樣的當代議題
- 教授 Python 數據科學堆疊中一些最重要工具的基本概念
- 提供對機率及其在統計中應用的基本但嚴謹的介紹
- 提供一個附屬網站,提供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 20 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. He has been an editor for IEEE Transactions on Wireless Communications, IEEE Wireless Communications magazine, and IEEE Transactions on Vehicular Technology.
作者簡介(中文翻譯)
約翰·M·謝亞(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20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。謝亞博士是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)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MILCOM非分類計劃中的最佳論文。他曾擔任IEEE無線通信期刊、IEEE無線通信雜誌和IEEE車輛技術期刊的編輯。