Practical Data Science with R (Paperback)
暫譯: 實用數據科學與 R
Nina Zumel, John Mount
- 出版商: Manning
- 出版日期: 2014-04-22
- 定價: $1,650
- 售價: 5.0 折 $825
- 語言: 英文
- 頁數: 389
- 裝訂: Paperback
- ISBN: 1617291560
- ISBN-13: 9781617291562
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相關分類:
R 語言、Data Science
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相關翻譯:
數據科學:理論、方法與R語言實踐 (簡中版)
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其他版本:
Practical Data Science with R, 2/e (Paperback)
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商品描述
Summary
Practical Data Science with R lives up to its name. It explains basic principles without the theoretical mumbo-jumbo and jumps right to the real use cases you'll face as you collect, curate, and analyze the data crucial to the success of your business. You'll apply the R programming language and statistical analysis techniques to carefully explained examples based in marketing, business intelligence, and decision support.
Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications.
About the Book
Business analysts and developers are increasingly collecting, curating, analyzing, and reporting on crucial business data. The R language and its associated tools provide a straightforward way to tackle day-to-day data science tasks without a lot of academic theory or advanced mathematics.
Practical Data Science with R shows you how to apply the R programming language and useful statistical techniques to everyday business situations. Using examples from marketing, business intelligence, and decision support, it shows you how to design experiments (such as A/B tests), build predictive models, and present results to audiences of all levels.
This book is accessible to readers without a background in data science. Some familiarity with basic statistics, R, or another scripting language is assumed.
What's Inside
- Data science for the business professional
- Statistical analysis using the R language
- Project lifecycle, from planning to delivery
- Numerous instantly familiar use cases
- Keys to effective data presentations
About the Authors
Nina Zumel and John Mount are cofounders of a San Francisco-based data science consulting firm. Both hold PhDs from Carnegie Mellon and blog on statistics, probability, and computer science at win-vector.com.
Table of Contents
PART 1 INTRODUCTION TO DATA SCIENCE
PART 2 MODELING METHODS
PART 3 DELIVERING RESULTS
- The data science process
- Loading data into R
- Exploring data
- Managing data
- Choosing and evaluating models
- Memorization methods
- Linear and logistic regression
- Unsupervised methods
- Exploring advanced methods
- Documentation and deployment
- Producing effective presentations
商品描述(中文翻譯)
**摘要**
《實用數據科學與 R》名副其實。它在沒有繁瑣理論的情況下解釋基本原則,直接進入您在收集、整理和分析對業務成功至關重要的數據時所面臨的實際案例。您將應用 R 程式語言和統計分析技術,仔細解釋基於行銷、商業智慧和決策支持的範例。
購買印刷書籍可獲得 Manning Publications 提供的免費 PDF、Kindle 和 ePub 格式電子書。
**關於本書**
商業分析師和開發人員越來越多地收集、整理、分析和報告關鍵商業數據。R 語言及其相關工具提供了一種簡單的方法來處理日常數據科學任務,而不需要大量的學術理論或高級數學。
《實用數據科學與 R》向您展示如何將 R 程式語言和有用的統計技術應用於日常商業情境。通過行銷、商業智慧和決策支持的範例,它展示了如何設計實驗(例如 A/B 測試)、建立預測模型,並向各級觀眾呈現結果。
本書適合沒有數據科學背景的讀者。假設讀者對基本統計、R 或其他腳本語言有一定的了解。
**內容概覽**
- 商業專業人士的數據科學
- 使用 R 語言的統計分析
- 專案生命週期,從規劃到交付
- 許多立即熟悉的使用案例
- 有效數據呈現的關鍵
**關於作者**
Nina Zumel 和 John Mount 是一家位於舊金山的數據科學諮詢公司的共同創辦人。兩人均持有卡內基梅隆大學的博士學位,並在 win-vector.com 上撰寫有關統計、概率和計算機科學的博客。
**目錄**
**第一部分 數據科學導論**
**第二部分 建模方法**
**第三部分 結果交付**
1. 數據科學過程
2. 將數據加載到 R 中
3. 探索數據
4. 管理數據
5. 選擇和評估模型
6. 記憶方法
7. 線性和邏輯回歸
8. 無監督方法
9. 探索高級方法
10. 文檔和部署
11. 產生有效的演示文稿