数理统计课程主页

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学生中心 (包含各类竞赛、考证、考研、及留学信息)．

鄂维南写的应用数学新时代的曙光．
谢益辉写的统计学简介．
知乎大V陈沁的回答．
知乎上的统计学话题索引．

导航栏：人工智能（右图1）
导航栏：机器学习与数据挖掘

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图书推荐：为什么、信号与噪声、女士品茶、数学之美．
电影推荐：点球成金、社交网络．

几个链接：

机器学习本质上属于应用统计学，更多地关注于如何用计算机统计地估计复杂函数，不太关注为这些函数提供置信区间．

—— 花书 第五章, by I. Goodfellow, Y. Bengio and A. Courville

Computer science as an academic discipline began in the 1960's. Emphasis was on programming languages, compilers, operating systems, and the mathematical theory that supported these areas. Courses in theoretical computer science covered finite automata, regular expressions, context-free languages, and computability. In the 1970's, the study of algorithms was added as an important component of theory. The emphasis was on making computers useful. Today, a fundamental change is taking place and the focus is more on a wealth of applications. ......

While traditional areas of computer science remain highly important, increasingly researchers of the future will be involved with using computers to understand and extract usable information from massive data arising in applications, not just how to make computers useful on specific well-defined problems. With this in mind we have written this book to cover the theory we expect to be useful in the next 40 years, just as an understanding of automata theory, algorithms, and related topics gave students an advantage in the last 40 years. One of the major changes is an increase in emphasis on probability, statistics, and numerical methods.

—— 数据科学基础 前言, by A. Blum, J. Hopcroft and R. Kannan