Data Science (Paperback)

John D. Kelleher, Brendan Tierney

  • 出版商: MIT
  • 出版日期: 2018-04-13
  • 售價: $760
  • 貴賓價: 9.5$722
  • 語言: 英文
  • 頁數: 280
  • 裝訂: Paperback
  • ISBN: 0262535432
  • ISBN-13: 9780262535434
  • 相關分類: Data Science
  • 相關翻譯: 人人可懂的數據科學 (簡中版)
  • 立即出貨 (庫存=1)

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商品描述

A concise introduction to the emerging field of data science, explaining its evolution, relation to machine learning, current uses, data infrastructure issues, and ethical challenges.

The goal of data science is to improve decision making through the analysis of data. Today data science determines the ads we see online, the books and movies that are recommended to us online, which emails are filtered into our spam folders, and even how much we pay for health insurance. This volume in the MIT Press Essential Knowledge series offers a concise introduction to the emerging field of data science, explaining its evolution, current uses, data infrastructure issues, and ethical challenges.

It has never been easier for organizations to gather, store, and process data. Use of data science is driven by the rise of big data and social media, the development of high-performance computing, and the emergence of such powerful methods for data analysis and modeling as deep learning. Data science encompasses a set of principles, problem definitions, algorithms, and processes for extracting non-obvious and useful patterns from large datasets. It is closely related to the fields of data mining and machine learning, but broader in scope. This book offers a brief history of the field, introduces fundamental data concepts, and describes the stages in a data science project. It considers data infrastructure and the challenges posed by integrating data from multiple sources, introduces the basics of machine learning, and discusses how to link machine learning expertise with real-world problems. The book also reviews ethical and legal issues, developments in data regulation, and computational approaches to preserving privacy. Finally, it considers the future impact of data science and offers principles for success in data science projects.

商品描述(中文翻譯)

一本簡明介紹新興領域「數據科學」的書籍,解釋其演變、與機器學習的關係、目前的應用、數據基礎設施問題和倫理挑戰。

數據科學的目標是通過數據分析來改進決策。如今,數據科學決定了我們在線上看到的廣告、推薦給我們的書籍和電影、哪些郵件被過濾到垃圾郵件文件夾中,甚至我們支付多少健康保險費。這本MIT Press Essential Knowledge系列的書提供了對新興領域數據科學的簡明介紹,解釋了其演變、目前的應用、數據基礎設施問題和倫理挑戰。

組織收集、存儲和處理數據從未如此容易。數據科學的使用受到大數據和社交媒體的崛起、高性能計算的發展以及深度學習等強大的數據分析和建模方法的出現的推動。數據科學涵蓋了一套從大型數據集中提取非明顯且有用模式的原則、問題定義、算法和流程。它與數據挖掘和機器學習領域密切相關,但範圍更廣。本書簡要介紹了該領域的歷史,介紹了基本的數據概念,並描述了數據科學項目的各個階段。它考慮了數據基礎設施以及整合來自多個來源的數據所帶來的挑戰,介紹了機器學習的基礎知識,並討論了如何將機器學習專業知識應用於現實問題。本書還回顧了倫理和法律問題、數據監管的發展以及保護隱私的計算方法。最後,它考慮了數據科學的未來影響,並提供了在數據科學項目中取得成功的原則。