The Data Science Handbook

Field Cady

  • 出版商: Wiley
  • 出版日期: 2017-02-28
  • 定價: $2,080
  • 售價: 9.0$1,872
  • 語言: 英文
  • 頁數: 416
  • 裝訂: Hardcover
  • ISBN: 1119092949
  • ISBN-13: 9781119092940
  • 相關分類: Data Science
  • 立即出貨

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商品描述

A comprehensive overview of data science covering the analytics, programming, and business skills necessary to master the discipline

Finding a good data scientist has been likened to hunting for a unicorn: the required combination of technical skills is simply very hard to find in one person. In addition, good data science is not just rote application of trainable skill sets; it requires the ability to think flexibly about all these areas and understand the connections between them. This book provides a crash course in data science, combining all the necessary skills into a unified discipline.

Unlike many analytics books, computer science and software engineering are given extensive coverage since they play such a central role in the daily work of a data scientist. The author also describes classic machine learning algorithms, from their mathematical foundations to real-world applications. Visualization tools are reviewed, and their central importance in data science is highlighted. Classical statistics is addressed to help readers think critically about the interpretation of data and its common pitfalls. The clear communication of technical results, which is perhaps the most undertrained of data science skills, is given its own chapter, and all topics are explained in the context of solving real-world data problems. The book also features:

• Extensive sample code and tutorials using Python™ along with its technical libraries

• Core technologies of “Big Data,” including their strengths and limitations and how they can be used to solve real-world problems

• Coverage of the practical realities of the tools, keeping theory to a minimum; however, when theory is presented, it is done in an intuitive way to encourage critical thinking and creativity

• A wide variety of case studies from industry

• Practical advice on the realities of being a data scientist today, including the overall workflow, where time is spent, the types of datasets worked on, and the skill sets needed

The Data Science Handbook is an ideal resource for data analysis methodology and big data software tools. The book is appropriate for people who want to practice data science, but lack the required skill sets. This includes software professionals who need to better understand analytics and statisticians who need to understand software. Modern data science is a unified discipline, and it is presented as such. This book is also an appropriate reference for researchers and entry-level graduate students who need to learn real-world analytics and expand their skill set.

FIELD CADY is the data scientist at the Allen Institute for Artificial Intelligence, where he develops tools that use machine learning to mine scientific literature. He has also worked at Google and several Big Data startups. He has a BS in physics and math from Stanford University, and an MS in computer science from Carnegie Mellon.

商品描述(中文翻譯)

一本全面介紹資料科學的書籍,涵蓋了掌握這一學科所需的分析、程式設計和商業技能。

找到一位優秀的資料科學家被形容為尋找獨角獸:所需的技術技能組合在一個人身上很難找到。此外,優秀的資料科學不僅僅是機械地應用可訓練的技能集合;它需要能夠靈活思考所有這些領域並理解它們之間的聯繫。本書提供了一個資料科學的速成課程,將所有必要的技能結合成一個統一的學科。

與許多分析書籍不同,計算機科學和軟體工程得到了廣泛的涵蓋,因為它們在資料科學家的日常工作中扮演著核心角色。作者還描述了經典的機器學習算法,從它們的數學基礎到實際應用。視覺化工具得到了評估,並突出了它們在資料科學中的重要性。傳統統計學被討論,以幫助讀者對數據的解釋和常見陷阱進行批判性思考。清晰地傳達技術結果,這可能是資料科學技能中最缺乏訓練的部分,有專門的章節介紹,並且所有主題都在解決實際的數據問題的背景下進行解釋。本書還包括:

- 使用Python及其技術庫的大量示例代碼和教程
- "大數據"的核心技術,包括它們的優點和局限性以及如何用於解決實際問題
- 將理論降到最低限度的工具的實際現實;然而,當理論被介紹時,以直觀的方式呈現,以鼓勵批判性思維和創造力
- 來自行業的各種案例研究
- 關於成為一名資料科學家的實際建議,包括整體工作流程、時間分配、處理的數據集類型和所需的技能組合

《資料科學手冊》是一個理想的資料分析方法和大數據軟體工具資源。本書適合希望從事資料科學但缺乏所需技能組合的人士。這包括需要更好地理解分析的軟體專業人士和需要理解軟體的統計學家。現代資料科學是一個統一的學科,本書以此為基礎進行介紹。本書也是研究人員和初級研究生學習實際分析和擴展技能組合的適當參考資料。

FIELD CADY是艾倫人工智能研究所的資料科學家,他開發了使用機器學習挖掘科學文獻的工具。他還曾在Google和幾家大數據初創公司工作。他擁有斯坦福大學的物理和數學學士學位,以及卡內基梅隆大學的計算機科學碩士學位。