2 数据预处理, data preprocessing

3 线性回归模型, linear regression model

https://docs.qq.com/pdf/DRHVxQndIWXZOTnFU

4 决策树与 K 最近邻算法, decision tree and k-nearest neigbors

https://docs.qq.com/pdf/DRHNsbk5oaEJWUHph

https://docs.qq.com/pdf/DRGNNU29VSWFKdWFY

5 参数线性分类模型与分类模型评估, parametric linear classifiers and classification model evaluation

https://docs.qq.com/pdf/DRHpncGNNcnBoekNU

6 感知机, perceptrons

https://docs.qq.com/pdf/DRHhLcmFpQWFnUWJa

7 支持向量机，support vector machines

https://docs.qq.com/pdf/DRG9GZ2xiSmNuckNK

8 逻辑回归，logistic regression

https://docs.qq.com/pdf/DRGtYVHdybVpZbE9w

9 人工神经网络, artificial neural networks

https://docs.qq.com/pdf/DRGFUcmtnR3FLWG5I

https://docs.qq.com/pdf/DREtaRmtoUkF6bUJm

10 贝叶斯学习：贝叶斯决策、朴素贝叶斯、线性判别分析, Bayesian learning: Bayesian prediction, naive Bayes, linear discriminative analysis

https://docs.qq.com/pdf/DRHJYeXRwamNESmxO

https://docs.qq.com/pdf/DRGxnbnJ3a2F0WnRj

11 降维算法：主成分分析、Fisher判别分析、自动编码器, dimensionality reduction: principal component analysis, Fisher discriminative analysis, auto-encoder

12 聚类算法：K均值算法、GMM算法, clustering: k-means algorithm, GMM

13 核方法，kernel methods

14 集成学习：随机森林、Adaboost、梯度提升算法, ensemble methods: random forests, Adaboost, gradient boosting algorithm

https://docs.qq.com/pdf/DRFFCa0paQUpFWUVW

15 生成模型：生成对抗网络、变分自动编码器、稳定扩散模型, generative models: GAN, variational auto-encoders, stable difussion models

16 机器学习实际应用中的问题, considerations of machine learning in practice