Adit Bhargava， 软件工程师，兼具计算机科学和美术方面的教育背景，在adit.io撰写编程方面的博客。
因为爱好，Adit踏入了编程殿堂。Visual Basic 6 for Dummies教会了他很多基础知识，但始终对算法没搞明白。直到遇到一位优秀的算法教授后，他才认识到这些概念是多么地简单且优雅。
Why would you like to write such an introductory book, which is full of fascinating scenarios and cute illustrations drawn by hand?
I usually take notes for myself when I learn something, because it helps me learn. For example here are the notes I'm taking as I read "A Book Of Abstract Algebra" (attached). So this was a technique I had used in the past, and I thought others might find it useful also. So I wrote this blog post. People liked it and it made me think that a book with the same style would probably do pretty well too.
（Let's enjoy Adit's explanation of Monad in pictures！）
Monad 将一个 “接受普通值并回传一个被封装值” 的函数应用到一个被封装的值上，这一任务由函数
half x = if even x then Just (x `div` 2) else Nothing
> Just 3 >>= half Nothing > Just 4 >>= half Just 2 > Nothing >>= half Nothing
class Monad m where (>>=) :: m a -> (a -> m b) -> m b
instance Monad Maybe where Nothing >>= func = Nothing Just val >>= func = func val
Just 20 >>= half >>= half >>= half会得到
（Taken from Adit's articleFunctors, Applicatives, And Monads In Pictures）
From the book cover, I thought it might be full of hand-drawn illustrations about mice. It seems not, for there’re other images like sheep, birds, rabbits, diagrams. Why would you put that picture in front of the book?
I wish I had a good answer for you! The people at Manning chose the picture on the cover. Manning was generally good about giving me a lot of control over the book, but for the cover, they really fell in love with this image and chose to use it.
A whole bunch of readers are really curious about your algorithmic teacher mentioned in author's introduction part who made tough concepts become simple but elegant. Could you share some of his/her teaching methods?
Sure! Her most effective teaching method was stepping through an algorithm line by line. When something is hard, it is easier skip over it. But in order to learn, it is important to slow down at the hard parts. So for each algorithm she taught, she would slow down and go through the code line by line and explain what each line did. I tried to do the same thing in my book. In the section on recursion, for example, I walk through each line and show how the stack changes. I think having that level of detail is really important.
What's your favorite algorithm? Why does it give you such a deep impression?
I've mentioned how much I love graph algorithms a few times in the book. Graphs are a really amazing structure that show up absolutely everywhere. I feel like I'm able to solve so many problems just using graph algorithms. I recently went to lunch with a friend and someone at the lunch said "I bet I can teach you Category Theory in 15 minutes". I didn't know anything about Category Theory, but I knew graphs and abstract algebra, so it actually took him less than five minutes to explain Category Theory to me. At work, I've been able to automate some tedious tasks, all because I know how topological sort and breadth-first search work.
Sometimes, short operational time does not necessarily mean good performances. Except time, are there any other dimensions to judge algorithm?
Yes! I think ease of use is a pretty important metric. For example, there are plenty of machine learning techniques more advanced than KNN, but if you are just starting out with a problem, you might want to start with KNN even if you are a machine learning expert. If an algorithm is easy to think about, there are fewer places for bugs to hide. Once you start getting into more complicated algorithms like neural networks, if you run into a bug, it will take more time to figure out the cause because there are so many more moving parts, so more places for the bug to hide. When picking an algorithm and considering performance time, it is important to think about the performance of the programmer also! Easy to understand code is more maintainable and more likely to be bug-free.
There are actually a few teenagers who are reading your book. What do you think of learning algorithm from very early ages, like primary school ages or even earlier?
I think that makes a lot of sense. Programming is a way to be creative, just like painting or music. I learned programming pretty early and made video games and animations. The earlier you learn, the sooner you can work on your own projects!
Will you keep this up with a "Grokking" series covering other CS/Dev topics? Because we all love it.
I hope so! I need to think hard about what else I can write about :)