10 Math Concepts for Programmers
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Publicado 2023-04-21
#math #programming #top10
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🔖 Topics Covered
- Do programmers need math?
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- Linear algebra for programmers
- Boolean Algebra explained
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- How does Big-O notatio
Todos los comentarios (21)
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Mathematics are the result of mysterious powers that nobody understands, and which the unconscious recognition of beauty must play an important part. Out of an infinity of designs, a mathematician chooses one pattern for beauty's sake and brings it down to earth.
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1. Boolean algebra 2. Numeral systems 3. Floating points 4. Logarithms 5. Set Theory 6. Combinatorics 7. Graph Theory 8. Complexity Theory 9. Statistics 10. Linear Algebra Interestingly i learned all of these in college but barely remember anything.
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In my opinion the most important math class for programmers is discrete mathematics. They helped me understand recursion and stuff like that mathematically
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Small correction: the Big O notation doesn't specify how fast something is. A constant time complexity of O(1) doesn't mean that the operation/algorithm is fast, but that the speed is constant as the input scales. As a consequence, an O(n^2) algo can be faster than an O(n) algo, for some range of small inputs.
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Dude, your examples are so much better than anything we ever got at school. I kinda wanna become a teacher just to be as good as you one day.
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Please do more such videos on computer science fundamentals. Like how compilers work, how interrupts work, internal working of CPU, network fundamentals, OS fundamentals, etc.
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I hated math in school, I avoided learning complex equations and algorithms when first learning to program, but once I saw a few of Sebastian Lagues videos where he does stuff in Unity, and started messing around with equations and learning to translate them from paper to code, I literally began to feel like I'm casting magic. Its so amazing what just a few dependent variables can change
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I paused the video in the middle just to say, that was the greatest explanation of logarithmic functions I've ever seen in my entire life, thank you for gracing me with that analogy and visual
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As a Asian Student, I can confirm you that we have learned all those math without knowing any use of it. 🙂
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4:10 In math it's more common to use a different base (ln(x)), but it's easy to change by multiplying the result by a factor, so it's not really important if you're working in base 2, 10, or Euler's number.
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Very interesting and informative video. Very rarely does fireship ever miss, but some videos feel like they fall into a more repetitive format of namedropping a bunch of languages and frameworks loosely tied to a relevant topic. You're very good at explaining topics that can be hard to visualize, I hope you do more videos on general concepts
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I feel like if teachers introduced some concepts as you introduced them here ppl would understand some things way faster, you've done some really nice visual aids, good job!
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In an era of AI related content on this channel, I'm so relaxed to see a normal non-AI video recently!
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Functional programming is still very closely attached to its mathematical roots and it makes programming experience beautiful.
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I'm currently studying Graph Theory for a test in the 2nd year of uni. And looking at my future classes everything matches up to what you said in this video! Amazing.
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This was one of the most important and interesting videos of my (fresh) coding career and even my whole education. I wish I had teachers that could share their knowledge in this way because I could rarely connect to them and had to learn the things on my own(the hard way). Thanks again, I wish I could subscribe more times as my behind is too poor to give any other kind of support.
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I love this! You did a really good job making these subjects relatable and show how important they are in computer science and software engineering.
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More math concepts for programmers: - Modular arithmetic (RSA encryption) - Differential geometry (smooth surfaces and curves) - Lambda calculus (functional programming) - Fourier transformation (image/audio compression & filtering) - Information theory (data compression) - Game theory (artifical intelligence) - Quaternions (computer graphics)
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As a first year undergrad studying Applied Math who has much interest in Computers, I enjoyed this video a lot! I'm currently studying Abstract Algebra and boy that thing is so tough to grasp.
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that log cut in half analogy was so practical and good. m never forgetting log graph in my life
