The Data Science Design Manual (Texts in Computer Science)

Steven S. Skiena

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商品描述

This engaging and clearly written textbook/reference provides a must-have introduction to the rapidly emerging interdisciplinary field of data science. It focuses on the principles fundamental to becoming a good data scientist and the key skills needed to build systems for collecting, analyzing, and interpreting data.

The Data Science Design Manual is a source of practical insights that highlights what really matters in analyzing data, and provides an intuitive understanding of how these core concepts can be used. The book does not emphasize any particular programming language or suite of data-analysis tools, focusing instead on high-level discussion of important design principles.

This easy-to-read text ideally serves the needs of undergraduate and early graduate students embarking on an “Introduction to Data Science” course. It reveals how this discipline sits at the intersection of statistics, computer science, and machine learning, with a distinct heft and character of its own. Practitioners in these and related fields will find this book perfect for self-study as well.

 

 

Additional learning tools:

 

  • Contains “War Stories,” offering perspectives on how data science applies in the real world
  • Includes “Homework Problems,” providing a wide range of exercises and projects for self-study
  • Provides a complete set of lecture slides and online video lectures at www.data-manual.com
  • Provides “Take-Home Lessons,” emphasizing the big-picture concepts to learn from each chapter
  • Recommends exciting “Kaggle Challenges” from the online platform Kaggle
  • Highlights “False Starts,” revealing the subtle reasons why certain approaches fail
  • Offers examples taken from the data science television show “The Quant Shop” (www.quant-shop.com)

 

 

 

 

 

 

 

 

 

 

商品描述(中文翻譯)

這本引人入勝且寫得清晰的教科書/參考書,提供了對快速崛起的跨學科領域「資料科學」的必備介紹。它專注於成為一名優秀的資料科學家所需的基本原則,以及建立收集、分析和解釋資料系統所需的關鍵技能。

《資料科學設計手冊》是一本提供實用見解的資料科學指南,強調在分析資料時真正重要的事情,並提供對這些核心概念的直觀理解。該書不強調任何特定的程式語言或資料分析工具套件,而是專注於高層次討論重要的設計原則。

這本易於閱讀的教材非常適合大學本科生和研究生開始進行「資料科學導論」課程的需求。它揭示了這個學科如何處於統計學、計算機科學和機器學習的交叉點,具有自己獨特的重要性和特點。從事這些及相關領域的從業人員也會發現這本書非常適合自學。

附加學習工具:
- 包含「戰爭故事」,提供資料科學在現實世界中的應用觀點
- 包含「作業問題」,提供各種練習和自學專案
- 提供完整的講義和線上視頻講座,網址為 www.data-manual.com
- 提供「帶回家的教訓」,強調每章所學的整體概念
- 推薦來自線上平台 Kaggle 的刺激「Kaggle 挑戰」
- 突顯「失敗的開始」,揭示某些方法失敗的微妙原因
- 提供來自資料科學電視節目「The Quant Shop」的範例,網址為 www.quant-shop.com