/Statistical-Methods-and-Machine-Learning

2021 Spring (Statistical Methods and Machine Learning) 统计方法与机器学习

Primary LanguageJupyter Notebook

Statistical-Methods-and-Machine-Learning

2021 Spring (Statistical Methods and Machine Learning) 统计方法与机器学习@DaSE, ECNU

统计方法和机器学习这两个部分完全是两回事

内容包含

  1. 统计方法实验
    1. One-Way-ANOVA(单因子方差分析)
    2. Variance-Stabilizing(方差稳定化变换)
    3. Two-Way-ANOVA(双因子方差分析)
    4. Simple-Linear-Regression(简单线性回归)
    5. Multiple-Linear-Regression(多重线性回归)
    6. Bias, Variance, MSE Simulation
    7. Multicolinearity(多重共线性)
    8. Principal-Component-Regression(主成分回归)
    9. Ridge-Regression(岭回归)
  2. 机器学习实验
    1. PCA & KNN based MNIST Recognition(基于主成分分析和K近邻算法的手写数字识别)
    2. News Classification based on Naive Bayes(基于朴素贝叶斯的新闻文本分类)
    3. Face Recognition(简易人脸识别)
  3. 机器学习理论作业

参考资料

  1. Stanford cs 229 Machine Learning CheatSheet
  2. Datawhale China 统计学习方法习题解答
  3. UC Irvine Machine Learning Data Sets