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ApacheCN 数据科学译文集 2020.8

协议:CC BY-NC-SA 4.0(http://creativecommons.org/licenses/by-nc-sa/4.0/)

不要担心自己的形象,只关心如何实现目标。——《原则》,生活原则 2.3.c

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  • ApacheCN 学习资源(http://www.apachecn.org/)

目录

  • TutorialsPoint NumPy 教程(https://github.com/apachecn/apachecn-ds-zh/blob/master/docs/tutorialspoint-numpy.md)

  • NumPy 秘籍中文第二版(https://github.com/apachecn/apachecn-ds-zh/blob/master/docs/numpy-cookbook-2e/README.md)

    • 零、前言(https://github.com/apachecn/apachecn-ds-zh/blob/master/docs/numpy-cookbook-2e/ch00.md)

    • 一、使用 IPython(https://github.com/apachecn/apachecn-ds-zh/blob/master/docs/numpy-cookbook-2e/ch01.md)

    • 二、高级索引和数组概念(https://github.com/apachecn/apachecn-ds-zh/blob/master/docs/numpy-cookbook-2e/ch02.md)

    • 三、掌握常用函数(https://github.com/apachecn/apachecn-ds-zh/blob/master/docs/numpy-cookbook-2e/ch03.md)

    • 四、将 NumPy 与世界的其他地方连接(https://github.com/apachecn/apachecn-ds-zh/blob/master/docs/numpy-cookbook-2e/ch04.md)

    • 五、音频和图像处理(https://github.com/apachecn/apachecn-ds-zh/blob/master/docs/numpy-cookbook-2e/ch05.md)

    • 六、特殊数组和通用函数(https://github.com/apachecn/apachecn-ds-zh/blob/master/docs/numpy-cookbook-2e/ch06.md)

    • 七、性能分析和调试(https://github.com/apachecn/apachecn-ds-zh/blob/master/docs/numpy-cookbook-2e/ch07.md)

    • 八、质量保证(https://github.com/apachecn/apachecn-ds-zh/blob/master/docs/numpy-cookbook-2e/ch08.md)

    • 九、使用 Cython 加速代码(https://github.com/apachecn/apachecn-ds-zh/blob/master/docs/numpy-cookbook-2e/ch09.md)

    • 十、Scikits 的乐趣(https://github.com/apachecn/apachecn-ds-zh/blob/master/docs/numpy-cookbook-2e/ch10.md)

    • 十一、最新最强的 NumPy(https://github.com/apachecn/apachecn-ds-zh/blob/master/docs/numpy-cookbook-2e/ch11.md)

    • 十二、使用 NumPy 进行探索性和预测性数据分析(https://github.com/apachecn/apachecn-ds-zh/blob/master/docs/numpy-cookbook-2e/ch12.md)

  • NumPy 初学者指南中文第三版(https://github.com/apachecn/apachecn-ds-zh/blob/master/docs/numpy-beginners-guide-3e/README.md)

    • 零、前言(https://github.com/apachecn/apachecn-ds-zh/blob/master/docs/numpy-beginners-guide-3e/ch00.md)

    • 一、NumPy 快速入门(https://github.com/apachecn/apachecn-ds-zh/blob/master/docs/numpy-beginners-guide-3e/ch01.md)

    • 二、从 NumPy 基本原理开始(https://github.com/apachecn/apachecn-ds-zh/blob/master/docs/numpy-beginners-guide-3e/ch02.md)

    • 三、熟悉常用函数(https://github.com/apachecn/apachecn-ds-zh/blob/master/docs/numpy-beginners-guide-3e/ch03.md)

    • 四、为您带来便利的便利函数(https://github.com/apachecn/apachecn-ds-zh/blob/master/docs/numpy-beginners-guide-3e/ch04.md)

    • 五、使用矩阵和 ufunc(https://github.com/apachecn/apachecn-ds-zh/blob/master/docs/numpy-beginners-guide-3e/ch05.md)

    • 六、深入探索 NumPy 模块(https://github.com/apachecn/apachecn-ds-zh/blob/master/docs/numpy-beginners-guide-3e/ch06.md)

    • 七、了解特殊例程(https://github.com/apachecn/apachecn-ds-zh/blob/master/docs/numpy-beginners-guide-3e/ch07.md)

    • 八、通过测试确保质量(https://github.com/apachecn/apachecn-ds-zh/blob/master/docs/numpy-beginners-guide-3e/ch08.md)

    • 九、matplotlib 绘图(https://github.com/apachecn/apachecn-ds-zh/blob/master/docs/numpy-beginners-guide-3e/ch09.md)

    • 十、当 NumPy 不够用时 - SciPy 及更多(https://github.com/apachecn/apachecn-ds-zh/blob/master/docs/numpy-beginners-guide-3e/ch10.md)

    • 十一、玩转 Pygame(https://github.com/apachecn/apachecn-ds-zh/blob/master/docs/numpy-beginners-guide-3e/ch11.md)

    • 附录 A:小测验答案(https://github.com/apachecn/apachecn-ds-zh/blob/master/docs/numpy-beginners-guide-3e/ch12.md)

    • 附录 B:其他在线资源(https://github.com/apachecn/apachecn-ds-zh/blob/master/docs/numpy-beginners-guide-3e/ch13.md)

    • 附录 C:NumPy 函数的参考(https://github.com/apachecn/apachecn-ds-zh/blob/master/docs/numpy-beginners-guide-3e/ch14.md)

  • NumPy 基础知识(https://github.com/apachecn/apachecn-ds-zh/blob/master/docs/numpy-essentials/README.md)

    • 零、前言(https://github.com/apachecn/apachecn-ds-zh/blob/master/docs/numpy-essentials/0.md)

    • 一、NumPy 简介(https://github.com/apachecn/apachecn-ds-zh/blob/master/docs/numpy-essentials/1.md)

    • 二、NumPy ndarray对象(https://github.com/apachecn/apachecn-ds-zh/blob/master/docs/numpy-essentials/2.md)

    • 三、使用 NumPy 数组(https://github.com/apachecn/apachecn-ds-zh/blob/master/docs/numpy-essentials/3.md)

    • 四、NumPy 核心和子模块(https://github.com/apachecn/apachecn-ds-zh/blob/master/docs/numpy-essentials/4.md)

    • 五、NumPy 中的线性代数(https://github.com/apachecn/apachecn-ds-zh/blob/master/docs/numpy-essentials/5.md)

    • 六、NumPy 中的傅立叶分析(https://github.com/apachecn/apachecn-ds-zh/blob/master/docs/numpy-essentials/6.md)

    • 七、构建和分发 NumPy 代码(https://github.com/apachecn/apachecn-ds-zh/blob/master/docs/numpy-essentials/7.md)

    • 八、使用 Cython 加速 NumPy(https://github.com/apachecn/apachecn-ds-zh/blob/master/docs/numpy-essentials/8.md)

    • 九、NumPy C-API 简介(https://github.com/apachecn/apachecn-ds-zh/blob/master/docs/numpy-essentials/9.md)

    • 十、扩展阅读(https://github.com/apachecn/apachecn-ds-zh/blob/master/docs/numpy-essentials/10.md)

  • 精通 NumPy 数值分析(https://github.com/apachecn/apachecn-ds-zh/blob/master/docs/master-num-comp-numpy/README.md)

    • 零、前言(https://github.com/apachecn/apachecn-ds-zh/blob/master/docs/master-num-comp-numpy/0.md)

    • 一、使用 NumPy 数组(https://github.com/apachecn/apachecn-ds-zh/blob/master/docs/master-num-comp-numpy/1.md)

    • 二、NumPy 线性代数(https://github.com/apachecn/apachecn-ds-zh/blob/master/docs/master-num-comp-numpy/2.md)

    • 三、使用 NumPy 统计函数对波士顿住房数据进行探索性数据分析(https://github.com/apachecn/apachecn-ds-zh/blob/master/docs/master-num-comp-numpy/3.md)

    • 四、使用线性回归预测房价(https://github.com/apachecn/apachecn-ds-zh/blob/master/docs/master-num-comp-numpy/4.md)

    • 五、使用 NumPy 对批发分销商的客户进行聚类(https://github.com/apachecn/apachecn-ds-zh/blob/master/docs/master-num-comp-numpy/5.md)

    • 六、NumPy,SciPy,Pandas 和 Scikit-Learn(https://github.com/apachecn/apachecn-ds-zh/blob/master/docs/master-num-comp-numpy/6.md)

    • 七、高级 NumPy(https://github.com/apachecn/apachecn-ds-zh/blob/master/docs/master-num-comp-numpy/7.md)

    • 八、高性能数值计算库概述(https://github.com/apachecn/apachecn-ds-zh/blob/master/docs/master-num-comp-numpy/8.md)

    • 九、性能基准(https://github.com/apachecn/apachecn-ds-zh/blob/master/docs/master-num-comp-numpy/9.md)

  • NumPy 数组学习手册(https://github.com/apachecn/apachecn-ds-zh/blob/master/docs/learn-numpy-array/README.md)

    • 零、前言(https://github.com/apachecn/apachecn-ds-zh/blob/master/docs/learn-numpy-array/0.md)

    • 一、NumPy 入门(https://github.com/apachecn/apachecn-ds-zh/blob/master/docs/learn-numpy-array/1.md)

    • 二、NumPy 基础(https://github.com/apachecn/apachecn-ds-zh/blob/master/docs/learn-numpy-array/2.md)

    • 三、使用 NumPy 的基本数据分析(https://github.com/apachecn/apachecn-ds-zh/blob/master/docs/learn-numpy-array/3.md)

    • 四、使用 NumPy 的简单预测性分析(https://github.com/apachecn/apachecn-ds-zh/blob/master/docs/learn-numpy-array/4.md)

    • 五、信号处理技术(https://github.com/apachecn/apachecn-ds-zh/blob/master/docs/learn-numpy-array/5.md)

    • 六、性能分析,调试和测试(https://github.com/apachecn/apachecn-ds-zh/blob/master/docs/learn-numpy-array/6.md)

    • 七、Python 科学生态系统(https://github.com/apachecn/apachecn-ds-zh/blob/master/docs/learn-numpy-array/7.md)

  • 精通 SciPy(https://github.com/apachecn/apachecn-ds-zh/blob/master/docs/master-scipy/README.md)

    • 零、前言(https://github.com/apachecn/apachecn-ds-zh/blob/master/docs/master-scipy/0.md)

    • 一、数值线性代数(https://github.com/apachecn/apachecn-ds-zh/blob/master/docs/master-scipy/1.md)

    • 二、插值和近似(https://github.com/apachecn/apachecn-ds-zh/blob/master/docs/master-scipy/2.md)

    • 三、微分与积分(https://github.com/apachecn/apachecn-ds-zh/blob/master/docs/master-scipy/3.md)

    • 四、非线性方程式和最优化(https://github.com/apachecn/apachecn-ds-zh/blob/master/docs/master-scipy/4.md)

    • 五、常微分方程的初值问题(https://github.com/apachecn/apachecn-ds-zh/blob/master/docs/master-scipy/5.md)

    • 六、计算几何(https://github.com/apachecn/apachecn-ds-zh/blob/master/docs/master-scipy/6.md)

    • 七、描述性统计(https://github.com/apachecn/apachecn-ds-zh/blob/master/docs/master-scipy/7.md)

    • 八、推断和数据分析(https://github.com/apachecn/apachecn-ds-zh/blob/master/docs/master-scipy/8.md)

    • 九、数字图像处理(https://github.com/apachecn/apachecn-ds-zh/blob/master/docs/master-scipy/9.md)

  • Pandas 秘籍(https://github.com/apachecn/apachecn-ds-zh/blob/master/docs/pandas-cookbook/README.md)

    • 零、前言(https://github.com/apachecn/apachecn-ds-zh/blob/master/docs/pandas-cookbook/ch00.md)

    • 一、Pandas 基础(https://github.com/apachecn/apachecn-ds-zh/blob/master/docs/pandas-cookbook/ch01.md)

    • 二、数据帧基本操作(https://github.com/apachecn/apachecn-ds-zh/blob/master/docs/pandas-cookbook/ch02.md)

    • 三、开始数据分析(https://github.com/apachecn/apachecn-ds-zh/blob/master/docs/pandas-cookbook/ch03.md)

    • 四、选择数据子集(https://github.com/apachecn/apachecn-ds-zh/blob/master/docs/pandas-cookbook/ch04.md)

    • 五、布尔索引(https://github.com/apachecn/apachecn-ds-zh/blob/master/docs/pandas-cookbook/ch05.md)

    • 六、索引对齐(https://github.com/apachecn/apachecn-ds-zh/blob/master/docs/pandas-cookbook/ch06.md)

    • 七、分组以进行汇总,过滤和转换(https://github.com/apachecn/apachecn-ds-zh/blob/master/docs/pandas-cookbook/ch07.md)

    • 八、将数据重组为整齐的表格(https://github.com/apachecn/apachecn-ds-zh/blob/master/docs/pandas-cookbook/ch08.md)

    • 九、组合 Pandas 对象(https://github.com/apachecn/apachecn-ds-zh/blob/master/docs/pandas-cookbook/ch09.md)

    • 十、时间序列分析(https://github.com/apachecn/apachecn-ds-zh/blob/master/docs/pandas-cookbook/ch10.md)

    • 十一、Pandas,Matplotlib 和 Seaborn 的可视化(https://github.com/apachecn/apachecn-ds-zh/blob/master/docs/pandas-cookbook/ch11.md)

  • Pandas 学习手册中文第二版(https://github.com/apachecn/apachecn-ds-zh/blob/master/docs/learning-pandas-2e/README.md)

    • 零、前言(https://github.com/apachecn/apachecn-ds-zh/blob/master/docs/learning-pandas-2e/0.md)

    • 一、Pandas 与数据分析(https://github.com/apachecn/apachecn-ds-zh/blob/master/docs/learning-pandas-2e/1.md)

    • 二、启动和运行 Pandas(https://github.com/apachecn/apachecn-ds-zh/blob/master/docs/learning-pandas-2e/2.md)

    • 三、用序列表示单变量数据(https://github.com/apachecn/apachecn-ds-zh/blob/master/docs/learning-pandas-2e/3.md)

    • 四、用数据帧表示表格和多元数据(https://github.com/apachecn/apachecn-ds-zh/blob/master/docs/learning-pandas-2e/4.md)

    • 五、数据帧的结构操作(https://github.com/apachecn/apachecn-ds-zh/blob/master/docs/learning-pandas-2e/5.md)

    • 六、索引数据(https://github.com/apachecn/apachecn-ds-zh/blob/master/docs/learning-pandas-2e/6.md)

    • 七、类别数据(https://github.com/apachecn/apachecn-ds-zh/blob/master/docs/learning-pandas-2e/7.md)

    • 八、数值统计方法(https://github.com/apachecn/apachecn-ds-zh/blob/master/docs/learning-pandas-2e/8.md)

    • 九、存取数据(https://github.com/apachecn/apachecn-ds-zh/blob/master/docs/learning-pandas-2e/9.md)

    • 十、整理数据(https://github.com/apachecn/apachecn-ds-zh/blob/master/docs/learning-pandas-2e/10.md)

    • 十一、合并,连接和重塑数据(https://github.com/apachecn/apachecn-ds-zh/blob/master/docs/learning-pandas-2e/11.md)

    • 十二、数据聚合(https://github.com/apachecn/apachecn-ds-zh/blob/master/docs/learning-pandas-2e/12.md)

    • 十三、时间序列建模(https://github.com/apachecn/apachecn-ds-zh/blob/master/docs/learning-pandas-2e/13.md)

    • 十四、可视化(https://github.com/apachecn/apachecn-ds-zh/blob/master/docs/learning-pandas-2e/14.md)

    • 十五、历史股价分析(https://github.com/apachecn/apachecn-ds-zh/blob/master/docs/learning-pandas-2e/15.md)

  • 精通 Pandas(https://github.com/apachecn/apachecn-ds-zh/blob/master/docs/master-pandas/README.md)

    • 零、前言(https://github.com/apachecn/apachecn-ds-zh/blob/master/docs/master-pandas/0.md)

    • 一、Pandas 和数据分析简介(https://github.com/apachecn/apachecn-ds-zh/blob/master/docs/master-pandas/1.md)

    • 二、Pandas 安装和支持软件(https://github.com/apachecn/apachecn-ds-zh/blob/master/docs/master-pandas/2.md)

    • 三、Pandas 数据结构(https://github.com/apachecn/apachecn-ds-zh/blob/master/docs/master-pandas/3.md)

    • 四、Pandas 的操作,第一部分 – 索引和选择(https://github.com/apachecn/apachecn-ds-zh/blob/master/docs/master-pandas/4.md)

    • 五、Pandas 的操作,第二部分 – 数据的分组,合并和重塑(https://github.com/apachecn/apachecn-ds-zh/blob/master/docs/master-pandas/5.md)

    • 六、处理缺失数据,时间序列和 Matplotlib 绘图(https://github.com/apachecn/apachecn-ds-zh/blob/master/docs/master-pandas/6.md)

    • 七、统计之旅 – 经典方法(https://github.com/apachecn/apachecn-ds-zh/blob/master/docs/master-pandas/7.md)

    • 八、贝叶斯统计简介(https://github.com/apachecn/apachecn-ds-zh/blob/master/docs/master-pandas/8.md)

    • 九、Pandas 库体系结构(https://github.com/apachecn/apachecn-ds-zh/blob/master/docs/master-pandas/9.md)

    • 十、R 与 Pandas 的比较(https://github.com/apachecn/apachecn-ds-zh/blob/master/docs/master-pandas/10.md)

    • 十一、机器学习简介(https://github.com/apachecn/apachecn-ds-zh/blob/master/docs/master-pandas/11.md)

  • NumPy 和 Pandas 数据分析实用指南(https://github.com/apachecn/apachecn-ds-zh/blob/master/docs/handson-data-analysis-numpy-pandas/README.md)

    • 零、前言(https://github.com/apachecn/apachecn-ds-zh/blob/master/docs/handson-data-analysis-numpy-pandas/0.md)

    • 一、配置 Python 数据分析环境(https://github.com/apachecn/apachecn-ds-zh/blob/master/docs/handson-data-analysis-numpy-pandas/1.md)

    • 二、探索 NumPy(https://github.com/apachecn/apachecn-ds-zh/blob/master/docs/handson-data-analysis-numpy-pandas/2.md)

    • 三、NumPy 数组上的运算(https://github.com/apachecn/apachecn-ds-zh/blob/master/docs/handson-data-analysis-numpy-pandas/3.md)

    • 四、Pandas 很有趣!什么是 Pandas?(https://github.com/apachecn/apachecn-ds-zh/blob/master/docs/handson-data-analysis-numpy-pandas/4.md)

    • 五、Pandas 的算术,函数应用以及映射(https://github.com/apachecn/apachecn-ds-zh/blob/master/docs/handson-data-analysis-numpy-pandas/5.md)

    • 六、排序,索引和绘图(https://github.com/apachecn/apachecn-ds-zh/blob/master/docs/handson-data-analysis-numpy-pandas/6.md)

  • 精通 Pandas 探索性分析(https://github.com/apachecn/apachecn-ds-zh/blob/master/docs/master-exp-analysis-pandas/README.md)

    • 零、前言(https://github.com/apachecn/apachecn-ds-zh/blob/master/docs/master-exp-analysis-pandas/0.md)

    • 一、处理不同种类的数据集(https://github.com/apachecn/apachecn-ds-zh/blob/master/docs/master-exp-analysis-pandas/1.md)

    • 二、数据选择(https://github.com/apachecn/apachecn-ds-zh/blob/master/docs/master-exp-analysis-pandas/2.md)

    • 三、处理,转换和重塑数据(https://github.com/apachecn/apachecn-ds-zh/blob/master/docs/master-exp-analysis-pandas/3.md)

    • 四、像专业人士一样可视化数据(https://github.com/apachecn/apachecn-ds-zh/blob/master/docs/master-exp-analysis-pandas/4.md)

  • Matplotlib 3.0 秘籍(https://github.com/apachecn/apachecn-ds-zh/blob/master/docs/matplotlib-30-cookbook/README.md)

    • 零、前言(https://github.com/apachecn/apachecn-ds-zh/blob/master/docs/matplotlib-30-cookbook/0.md)

    • 一、Matplotlib 的剖析(https://github.com/apachecn/apachecn-ds-zh/blob/master/docs/matplotlib-30-cookbook/1.md)

    • 二、基本绘图入门(https://github.com/apachecn/apachecn-ds-zh/blob/master/docs/matplotlib-30-cookbook/2.md)

    • 三、绘制多个图表和子图(https://github.com/apachecn/apachecn-ds-zh/blob/master/docs/matplotlib-30-cookbook/3.md)

    • 四、开发可视化来提高发布质量(https://github.com/apachecn/apachecn-ds-zh/blob/master/docs/matplotlib-30-cookbook/4.md)

    • 五、使用高级功能的绘图(https://github.com/apachecn/apachecn-ds-zh/blob/master/docs/matplotlib-30-cookbook/5.md)

    • 六、嵌入文本和表达式(https://github.com/apachecn/apachecn-ds-zh/blob/master/docs/matplotlib-30-cookbook/6.md)

    • 七、以不同格式保存图形(https://github.com/apachecn/apachecn-ds-zh/blob/master/docs/matplotlib-30-cookbook/7.md)

    • 八、开发交互式绘图(https://github.com/apachecn/apachecn-ds-zh/blob/master/docs/matplotlib-30-cookbook/8.md)

    • 九、在图形用户界面中嵌入绘图(https://github.com/apachecn/apachecn-ds-zh/blob/master/docs/matplotlib-30-cookbook/9.md)

    • 十、使用mplot3d工具包绘制 3D 图形(https://github.com/apachecn/apachecn-ds-zh/blob/master/docs/matplotlib-30-cookbook/10.md)

    • 十一、使用axisartist工具包(https://github.com/apachecn/apachecn-ds-zh/blob/master/docs/matplotlib-30-cookbook/11.md)

    • 十二、使用axes_grid1工具包(https://github.com/apachecn/apachecn-ds-zh/blob/master/docs/matplotlib-30-cookbook/12.md)

    • 十三、使用 Cartopy 工具包绘制地理地图(https://github.com/apachecn/apachecn-ds-zh/blob/master/docs/matplotlib-30-cookbook/13.md)

    • 十四、使用 Seaborn 工具包的探索性数据分析(https://github.com/apachecn/apachecn-ds-zh/blob/master/docs/matplotlib-30-cookbook/14.md)

  • Matplotlib 绘图秘籍(https://github.com/apachecn/apachecn-ds-zh/blob/master/docs/matplotlib-plot-cookbook/README.md)

    • 零、前言(https://github.com/apachecn/apachecn-ds-zh/blob/master/docs/matplotlib-plot-cookbook/ch00.md)

    • 一、第一步(https://github.com/apachecn/apachecn-ds-zh/blob/master/docs/matplotlib-plot-cookbook/ch01.md)

    • 二、自定义颜色和样式(https://github.com/apachecn/apachecn-ds-zh/blob/master/docs/matplotlib-plot-cookbook/ch02.md)

    • 三、处理标注(https://github.com/apachecn/apachecn-ds-zh/blob/master/docs/matplotlib-plot-cookbook/ch03.md)

    • 四、处理图形(https://github.com/apachecn/apachecn-ds-zh/blob/master/docs/matplotlib-plot-cookbook/ch04.md)

    • 五、文件输出(https://github.com/apachecn/apachecn-ds-zh/blob/master/docs/matplotlib-plot-cookbook/ch05.md)

    • 六、处理地图(https://github.com/apachecn/apachecn-ds-zh/blob/master/docs/matplotlib-plot-cookbook/ch06.md)

    • 七、处理 3D 图形(https://github.com/apachecn/apachecn-ds-zh/blob/master/docs/matplotlib-plot-cookbook/ch07.md)

    • 八、用户界面(https://github.com/apachecn/apachecn-ds-zh/blob/master/docs/matplotlib-plot-cookbook/ch08.md)

  • Sklearn 秘籍(https://github.com/apachecn/apachecn-ds-zh/blob/master/docs/sklearn-cookbook/README.md)

    • 第一章 模型预处理(https://github.com/apachecn/apachecn-ds-zh/blob/master/docs/sklearn-cookbook/1.md)

    • 第二章 处理线性模型(https://github.com/apachecn/apachecn-ds-zh/blob/master/docs/sklearn-cookbook/2.md)

    • 第三章 使用距离向量构建模型(https://github.com/apachecn/apachecn-ds-zh/blob/master/docs/sklearn-cookbook/3.md)

    • 第四章 使用 scikit-learn 对数据分类(https://github.com/apachecn/apachecn-ds-zh/blob/master/docs/sklearn-cookbook/4.md)

    • 第五章 模型后处理(https://github.com/apachecn/apachecn-ds-zh/blob/master/docs/sklearn-cookbook/5.md)

  • Sklearn 学习手册(https://github.com/apachecn/apachecn-ds-zh/blob/master/docs/learning-sklearn/README.md)

    • 一、机器学习 - 温和的介绍(https://github.com/apachecn/apachecn-ds-zh/blob/master/docs/learning-sklearn/ch01.md)

    • 二、监督学习(https://github.com/apachecn/apachecn-ds-zh/blob/master/docs/learning-sklearn/ch02.md)

    • 三、无监督学习(https://github.com/apachecn/apachecn-ds-zh/blob/master/docs/learning-sklearn/ch03.md)

    • 四、高级功能(https://github.com/apachecn/apachecn-ds-zh/blob/master/docs/learning-sklearn/ch04.md)

贡献指南

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联系方式

负责人

  • 飞龙(https://github.com/wizardforcel): 562826179

其他

  • 在我们的 apachecn/apachecn-ds-zh(https://github.com/apachecn/apachecn-ds-zh) github 上提 issue.

  • 在我们的 组织学习交流群(http://www.apachecn.org/organization/348.html) 中联系群主/管理员即可.

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