Hi, I'm Misaka Mikoto. I share some sweet hacker tips and ideas. 常盤台2年生の御坂美琴です。主にハッキングや機械学習などについてツイートしてます。海外の人にも読んでもらえるように、頑張って英語で書きますので、よろしくお願いします(^o^)

Academy City, Tama Area, Tokyo
Joined May 2015
A good implementation keeps similar components dependent on a master component such that mostly only the master needs to change.
String interpolation requires care to not escape special characters. Let this WeChat bug serve as a lesson.
One problem with trying to get other developers to work with your code is the fact that you have not written any documentation.
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Recursion may seem tricky to program. However, in practice it's usually easier but more inefficient than an iterative method.
If you want to solve a problem, Google it. Did that already? Good. Do it again.
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My classmates often ask me, "How did you become so leet?" That's when I tell them, "I watched 'Hackers'."
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If you find yourself needing to use your mouse while coding, then you should use vim. And don't use Windows.
When you don't know how to solve a problem involving computers, you should Google for the solution and read everything until you understand.
Nothing is better a lesson for buffer bounds checking than Heartbleed.
Overclocking doesn't just make your machine more awesome. It also increases the probability of experiencing an awesome meltdown.
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At Tokiwadai, if you get caught not properly indenting your code, you lose dorm privileges for a day.
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The simplex method isn't in polynomial time, but in practice it's faster than the currently known polynomial algorithm.
Q = (c97445f45cdef9f0d3e05e1e585fc297235b82b5be8ff3efca67c59852018192, b28ef557ba31dfcbdd21ac46e2a91e3c304f44cb87058ada2cb815151e610046)
A Gekota decal on my machine would be awesome.
Shiba Tatsuya is a script kiddie.
Machine learning has "machine" in it because I can't directly use it to study English. So frustrating...
Kamijō Tōma is a good-for-nothing idiot. Idiot idiot idiot.
I can confirm that integer factorization is in BQP. I just played with some qubits.
Convergence speed is important, but faster doesn't equal better.
In short, machine learning is using data to effectively train models to solve some problem.