数据准备和特征工程――数据工程师必知必会技能

本书详细地介绍了大数据、人工智能等项目中不可或缺的环节和内容：数据准备和特征工程。书中的每节首先以简明方式介绍了基本知识；然后通过实际案例演示了基本知识的实际应用，并提供了针对性练习项目，将“知识、案例、练习”融为一体；很后以“扩展探究”方式引导读者进入更深广的领域。本书既适合作为大学相关专业的教材，也适合作为大数据、人工智能等领域的开发人员的参考读物。

齐伟，自称老齐，现居苏州，所著在线教程《零基础学Python》及《零基础学Python（第2版）》在业内引起很好大的反响。愿意和来自各方的朋友讨论技术问题，并能提供相关技术服务。

目录 章 感知数据 ·································.0011.0 了解数据科学项目 ································0011.1 文件中的数据 ··································0031.1.1 CSV文件 ····································0031.1.2 Excel文件 ···································0091.1.3 图像文件 ···································0151.2 数据库中的数据 ·································0191.3 网页上的数据 ··································0291.4 来自API 的数据 ·································039第2 章 数据清理 ··································0442.0 基本概念 ····································0452.1 转化数据类型 ··································0462.2 处理重复数据 ··································0542.3 处理缺失数据 ··································0572.3.1 检查缺失数据 ·································0582.3.2 用指定值填补 ·································0632.3.3 根据规律填补 ·································0692.4 处理离群数据 ··································076第3 章 特征变换 ···································0833.0 特征的类型 ···································0843.1 特征数值化 ···································0853.2 特征二值化 ···································0883.3 OneHot编码 ···································0933.4 数据变换 ····································0983.5 特征离散化 ···································1043.5.1 无监督离散化 ·································1043.5.2 有监督离散化 ·································1103.6 数据规范化 ···································113第4 章 特征选择 ···································1244.0 特征选择简述 ··································1244.1 封装器法 ····································1274.1.1 循序特征选择 ·································1274.1.2 穷举特征选择 ·································1354.1.3 递归特征消除 ·································1404.2 过滤器法 ····································1444.3 嵌入法 ·····································149第5 章 特征抽取 ···································1545.1 无监督特征抽取··································1545.1.1 主成分分析 ··································1545.1.2 因子分析 ···································1615.2 有监督特征抽取 ·································167附录A Jupyter简介 ·································173附录B NumPy简介 ··································176附录C Pandas简介 ··································185附录D Matplotlib简介 ································194后记 ········································199