随机变量及其分布 参考 概率论与数理统计 课程即可 期望与方差 $$ \mathbb{E}[X] 和 Var(X) $$ 参考 概率论与数理统计 课程即可 随机变量的和 equality vs Identically distributed vs IID 有意思的分析 😏 期望和方差的性质 协方差与相关系数 伯努利（0-1）和Binomial分布 Sample Statistics sample mean central limit theorem

$\downarrow{shuffle}$ SGD: Stochastic Gradient Descent(but size == 1) convexity (凹凸性) feature engineering 在于怎么使用transforming feature function see website code non-numeric features one-hot encoding concat high order polynomials detect overfitting collect more data more see next lecture

Accuracy is a necessary, but not sufficient, condition for fair system. Fairness and transparency are context-dependent. Learn to work with contexts, and consider how your data analysis will reshape them. Keep in mind the power, and limits, of data analysis.