spark-ml-graph_day04_regression_20191021 torrent, magnet, bt

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spark-ml-graph_day04_regression_20191021

magnet:?xt=urn:btih:9F2A65C225B50F30E43840FE6769526CC1FF916A&dn=spark-ml-graph_day04_regression_20191021

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Torrent Hash:

9F2A65C225B50F30E43840FE6769526CC1FF916A

Number of Files:

117

Content Size:

1.09GB

Convert On:

2020-09-11

Keywords:

spark ml graph day04 regression 20191021

Magnet Link:

magnet:?xt=urn:btih:9F2A65C225B50F30E43840FE6769526CC1FF916A&dn=spark-ml-graph_day04_regression_20191021

Link:

//btsow.motorcycles/magnet/detail/hash/9F2A65C225B50F30E43840FE6769526CC1FF916A

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File Name

Size

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03_笔记/D-多元回归模型.png

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03_笔记/F-逻辑回归函数.png

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03_笔记/ML_GraphX_Day04：Regression.md

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06_资料/现实与理想机器学习.jpg

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03_笔记/A-简单线性回归方程（演变）.png

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03_笔记/C-损失函数和代价函数.png

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03_笔记/B-线性回归公式说明.png

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03_笔记/E-代价函数及GD梯度下降.png

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05_代码/day04-regression.zip

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165.83KB

05_代码/day03-features.zip

171.37KB

06_资料/机器学习路线图.jpg

556.34KB

01_讲义/0401-(线性回归和逻辑回归)SparkMllib回归问题理论及实战.pdf

3.62MB

02_视频/03-特征工程：PCA降维和ChiSqSelector选择.itcast

13.21MB

07_数据/datas.zip

17.09MB

02_视频/08-今天课程内容提纲：线性回归和逻辑回归.itcast

19.7MB

02_视频/11-线性回归原理：损失、代价及目标函数.itcast

20.43MB

02_视频/20-目标函数最优解求法：牛顿法.itcast

21.55MB

02_视频/09-线性回归原理：回归模型引入.itcast

22.38MB

02_视频/16-线性回归案例（官方）：房价预测（标准化特征）.itcast

24.25MB

02_视频/13-线性回归原理：BGD、SGD及MBGD.itcast

27.73MB

02_视频/19-官方案例代码演示（Lasso和Ridge回归）.itcast

28.64MB

02_视频/01-昨日课程内容回顾：基于DataFrame API构建ALS模型.itcast

30.94MB

02_视频/17-线性回归模型评估指标.itcast

38.9MB

02_视频/14-回顾多元线性回归算法要点核心.itcast

44.39MB

02_视频/18-线性回归算法（代价函数）正则化.itcast

47.2MB

02_视频/02-昨日课程内容回顾：特征工程.itcast

53.89MB

02_视频/06-波士顿房价预测，构建回归模型（二）.itcast

58.48MB

02_视频/15-线性回归案例（官方）：房价预测（基本算法）.itcast

58.48MB

02_视频/22-逻辑回归算法（sigmod函数及牛顿法）.itcast

59.89MB

02_视频/05-波士顿房价预测，构建回归模型（一）.itcast

63.19MB

02_视频/07-回归实战案例：构建回归模型（基于DataFrame API）.itcast

69.19MB

02_视频/12-线性回归原理：多元线性回归及梯度下降.itcast

71.32MB

02_视频/10-线性回归原理：线性回归公式（目标函数）.itcast

73.4MB

02_视频/04-分类实战案例：构建分类模型（基于DataFrame API）.itcast

76.57MB

02_视频/23-官方案例代码演示（逻辑回归二分类）.itcast

76.97MB

02_视频/21-基于DataFrame API的线性回归模型案例演示.itcast

88.83MB

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