數據準備和特徵工程——數據工程師必知必會技能

《數據準備和特徵工程——數據工程師必知必會技能》是2020年3月電子工業出版社出版的圖書，作者是齊偉。

基本介紹

• 中文名：數據準備和特徵工程——數據工程師必知必會技能
• 作者：齊偉
• ISBN：9787121382635
• 頁數：208頁
• 定價：45元
• 出版社：電子工業出版社
• 出版時間：2020年3月
• 開本：16開

內容簡介

本書詳細地介紹了大數據、人工智慧等項目中不可或缺的環節和內容：數據準備和特徵工程。書中的每節首先以簡明方式介紹了基本知識；然後通過實際案例演示了基本知識的實際套用，並提供了針對性練習項目，將“知識、案例、練習”融為一體；最後以“擴展探究”方式引導讀者進入更深廣的領域。本書既適合作為大學相關專業的教材，也適合作為大數據、人工智慧等領域的開發人員的參考讀物。

圖書目錄

目錄

第1 章 感知數據 ·································.001

1.0 了解數據科學項目 ································001

1.1 檔案中的數據 ··································003

1.1.1 CSV檔案 ····································003

1.1.2 Excel檔案 ···································009

1.1.3 圖像檔案 ···································015

1.2 資料庫中的數據 ·································019

1.3 網頁上的數據 ··································029

1.4 來自API 的數據 ·································039

第2 章 數據清理 ··································044

2.0 基本概念 ····································045

2.1 轉化數據類型 ··································046

2.2 處理重複數據 ··································054

2.3 處理缺失數據 ··································057

2.3.1 檢查缺失數據 ·································058

2.3.2 用指定值填補 ·································063

2.3.3 根據規律填補 ·································069

2.4 處理離群數據 ··································076

第3 章 特徵變換 ···································083

3.0 特徵的類型 ···································084

3.1 特徵數值化 ···································085

3.2 特徵二值化 ···································088

3.3 OneHot編碼 ···································093

3.4 數據變換 ····································098

3.5 特徵離散化 ···································104

3.5.1 無監督離散化 ·································104

3.5.2 有監督離散化 ·································110

3.6 數據規範化 ···································113

第4 章 特徵選擇 ···································124

4.0 特徵選擇簡述 ··································124

4.1 封裝器法 ····································127

4.1.1 循序特徵選擇 ·································127

4.1.2 窮舉特徵選擇 ·································135

4.1.3 遞歸特徵消除 ·································140

4.2 過濾器法 ····································144

4.3 嵌入法 ·····································149

第5 章 特徵抽取 ···································154

5.1 無監督特徵抽取··································154

5.1.1 主成分分析 ··································154

5.1.2 因子分析 ···································161

5.2 有監督特徵抽取 ·································167

附錄A Jupyter簡介 ·································173

附錄B NumPy簡介 ··································176

附錄C Pandas簡介 ··································185

附錄D Matplotlib簡介 ································194

後記 ········································199