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Cavill's Blog

Archives

All the articles I've archived.

202611
October2
  • 你需要一个更好的终端

    今天无意之间想起,自己至今没有配置过一个既好用又漂亮的终端,于是就动手配置了一下。这篇博客会详细记载我如何配置的过程。

  • 如何理解实变函数的上下极限?

    通过小恐龙跳台阶的例子,直观理解实数数列与集列的上极限、下极限:它们分别描述反复出现与最终恒定出现的值或元素,并给出尾部上确界、下确界和集合运算的严格定义。

August3
  • 为什么char *argv[]表示字符串?

    解释`char *argv[]表示字符串的原理`

  • CMake 入门

    从一个最小的 C++ 项目出发,理解 CMake 如何描述目标、生成构建系统并组织工程。

  • Dijkstra’s algorithm

    从贪心选择到代码实现,理解 Dijkstra 算法为何正确,以及它为何要求边权非负。

July6
  • Machine Learning:Tensor For Beginners

    从数据形状、矩阵梯度到雅可比矩阵,理解机器学习中的张量求导、输出轴与输入轴,以及反向传播的核心思路。

  • How Google Ranks the Web

    An intuitive guide to PageRank: how random walks, link structure, and the damping factor help Google rank pages across the web.

  • Chasing the Golden Snitch

    In the world of Quidditch, catching the Golden Snitch is not just a matter of speed. By viewing it as a moving target in an uncertain environment, we explore how search algorithms, Bayesian inference, and particle filters help a seeker locate what cannot be directly observed.

  • Implementing a Skip List from Scratch

    A step-by-step guide to implementing a Skip List in modern C++, covering its layered structure, randomized levels, and the search, insertion, and deletion operations.

  • Monty Hall problem

    A deep dive into the Monty Hall Problem. This article explains the famous probability puzzle using both intuitive case analysis and Bayes' theorem, showing why switching doors gives a 2/3 chance of winning and why human intuition often fails in probabilistic reasoning.

  • 从计算图理解反向传播

    An intuitive introduction to backpropagation through computational graphs, explaining how chain rule and dynamic programming make efficient gradient computation possible.