From dd5cba1286768887ae60b13e6544692be1a1a16a Mon Sep 17 00:00:00 2001 From: BarbarossaWang <40034814+BarbarossaWang@users.noreply.github.com> Date: Sun, 25 Sep 2022 19:29:38 +0800 Subject: [PATCH] fix description --- docs/数据结构与算法/Algo.en.md | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/docs/数据结构与算法/Algo.en.md b/docs/数据结构与算法/Algo.en.md index d1eada4b..ffacd31b 100644 --- a/docs/数据结构与算法/Algo.en.md +++ b/docs/数据结构与算法/Algo.en.md @@ -10,13 +10,13 @@ This is the highest rated algorithms course on [Coursera](https://www.coursera.org), and Professor Robert Sedgewick has a magic way of making even the most complex algorithms look incredibly vivid and simple. To be honest, the KMP and network flow algorithms that I have been struggling with for years were made clear to me in this course, and I can even write derivations and proofs for both of them two years later. -Do you think that after learning the algorithm, then you forget it? I think the core of letting you fully grasp an algorithm lies in understanding three points: +Do you feel that you have learned algorithms then forget them quickly? I think the key of letting you fully grasp an algorithm lies in understanding three points: - Why do you do this? (Correctness derivation, or the essence of the entire algorithm.) - How to implement it? (It is not enough to learn without practices.) - Use it to solve practical problems (Know how to apply you have learned is real skill.) -The composition of this course fits the three steps above very well. Watching the course videos and reading the professor's [textbook](https://algs4.cs.princeton.edu/home/) will help you understand the nature of the algorithm and allow you to tell others why the algorithm has to look like this in very vivid and simple terms . +The composition of this course fits the three points above very well. Watching the course videos and reading the professor's [textbook](https://algs4.cs.princeton.edu/home/) will help you understand the nature of the algorithm and allow you to tell others why the algorithm has to look like this in very vivid and simple terms . After understanding algorithms, you can read the professor's [code implementation](https://algs4.cs.princeton.edu/code/) of all the data structures and algorithms taught in the course. Note that these implementations are not demo, but industrial, efficient implementations. They are high-quality code that have rigorous annotations and variable names, and their modularization is also quite good. I learned a lot from these codes.