|__附件
|__机器学习算法PPT.pdf 9.87MB
|__数据-代码.txt 50B
|__python数据分析与机器学习实战
|__课时21.细节设置.flv_d.flv 45.94MB
|__课时178.应用聚类算法得出异常IP点.flv_d.flv 48.25MB
|__课时19.条形图与散点图.flv_d.flv 54.81MB
|__课时18.子图操作.flv_d.flv 64.30MB
|__课时20.柱形图与盒图.flv_d.flv 45.48MB
|__课时177.特征数据预处理.flv_d.flv 46.03MB
|__课时174.数据分析维度.flv_d.flv 51.44MB
|__课时173.数据对数变换.flv_d.flv 40.37MB
|__课时176.建立特征工程.flv_d.flv 44.58MB
|__课时175.变量关系可视化展示.flv_d.flv 96.75MB
|__课时170.数据切片分析.flv_d.flv 104.22MB
|__课时172.峰度与偏度.flv_d.flv 48.44MB
|__课时171.单变量分析.flv_d.flv 116.67MB
|__课时17.折线图绘制.flv 40.84MB
|__课时168.红牌和肤色的关系.flv_d.flv 128.35MB
|__课时169.数据背景简介.flv_d.flv 64.48MB
|__课时167.报表可视化分析.flv_d.flv 61.05MB
|__课时166.多特征之间关系分析.flv_d.flv 64.76MB
|__课时164.缺失值可视化分析.flv_d.flv 106.05MB
|__课时165.特征可视化展示.flv_d.flv 69.42MB
|__课时162.数据读取与预处理.flv_d.flv 72.11MB
|__课时163.数据切分模块.flv_d.flv 77.64MB
|__课时16.Series结构.flv_d.flv 77.15MB
|__课时161.数据背景介绍.flv 54.27MB
|__课时160.内容简介.flv_d.flv 7.77MB
|__课时159.应用阈值得出结果.flv_d.flv 30.68MB
