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斯坦福大学吴恩达机器学习课程学习笔记和原始讲义

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斯坦福大学吴恩达机器学习课程学习笔记和原始讲义
该课件为中科院一位同仁在学习斯坦福大学吴恩达机器学习课程是所做的学习笔记,非常好,吴老师上课掠过的一些内容笔记都详细给出,并且还做了适当补充,强烈推荐 本软件ID:10242914

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(41个子文件28.59MB)斯坦福大学吴恩达机器学习课程学习笔记和原始讲义
斯坦福大学吴恩达机器学习课程学习笔记和原始讲义
斯坦福大学机器学习课程原始讲义.zip 2.98MB
斯坦福大学机器学习课程个人学习笔记(下).zip 6.01MB
斯坦福大学机器学习课程个人学习笔记(上).zip 5.31MB
斯坦福大学机器学习课程个人学习笔记(下)
(13)因子分析.pdf 952.74KB
(14)增强学习.pdf 899.98KB
(15)典型关联分析.pdf 961.54KB
(10)主成分分析.pdf 1.72MB
(16)偏最小二乘法回归.pdf 279.08KB
请先查看该说明.txt 910B
(12)线性判别分析.pdf 918.07KB
(11)独立成分分析.pdf 905.68KB
(9)在线学习.pdf 530.77KB
斯坦福大学机器学习课程原始讲义
cs229-notes7a.pdf 264.67KB
cs229-notes9.pdf 81.16KB
cs229-gp.pdf 150.96KB
cs229-prob.pdf 147.50KB
cs229-linalg.pdf 164.59KB
cs229-cvxopt2.pdf 196.80KB
cs229-notes5.pdf 86.63KB
cs229-notes7b.pdf 53.89KB
cs229-notes1.pdf 229.65KB
ML-advice.pdf 313.47KB
cs229-notes10.pdf 75.40KB
cs229-notes12.pdf 73.96KB
cs229-notes4.pdf 108.74KB
cs229-notes3.pdf 175.57KB
cs229-hmm.pdf 197.80KB
cs229-notes8.pdf 81.18KB
cs229-cvxopt.pdf 148.86KB
cs229-notes11.pdf 74.18KB
cs229-notes6.pdf 50.85KB
cs229-notes2.pdf 858.17KB
斯坦福大学机器学习课程个人学习笔记(上)
(3)支持向量机SVM(上).pdf 877.86KB
(2)判别模型、生成模型与朴素贝叶斯方法.pdf 1.04MB
(7)混合高斯模型和EM算法.pdf 436.95KB
请先查看该说明.txt 910B
(1)线性回归、logistic回归和一般回归.pdf 842.55KB
(8)EM算法.pdf 757.24KB
(6)K-means聚类算法.pdf 532.76KB
(5)规则化和模型选择.pdf 895.02KB
(4)支持向量机SVM(下).pdf 1.15MB
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评论信息

  • zyf_1990:
    非常好的资源,谢谢分享2018-10-08

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