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maths can be like programming: it can seem pointless without a purpose. too much is made of proofs and too little of intuition. so pick a project, something yo

by dododo 16y ago

maths can be like programming: it can seem pointless without a purpose. too much is made of proofs and too little of intuition. so pick a project, something you'd like to know. then apply math as, and when, needed. what are you interested in? (other than learning math) if we know, then maybe someone can suggest a project related to something you'd care about :)

thesnark 16y ago
I agree with this. For me, math started to make sense when I saw it applied to problems, especially simple physics problems that explain things you can directly observe. The Feynman lectures were an especially rich source of these types of problems. My favorites: at what angle will a marble rolling down the side of a bowling ball leave the surface? when you observe water flowing out of your tap, the stream tappers and becomes more thin as it falls, can you derive the formula for that?
todayiamme 16y ago
Awesome. You nailed how I wanted to approach it. I am sorry if this comment sounds like a bunch of gibberish, but I am half asleep down here. I actually want to learn maths because I want to make this beautiful thing I have in my head. It's basically a user friendly data mining app that learns as you go along and it gives you the stuff you need. Not what I think you need. Basically I am trying to make a system that can collect data, and analyze it for someone who doesn't know what parameters to set in the first place. After that I want to apply what I learn from those interaction to trim the excess fat or give anything more if required. I know that this is a really lofty goal, but if I make it then I would be the happiest person on earth. As this is a part of an even bigger thing I want to make, which is brewing in my head. :) I haven't been able to get much mileage as I have concentration issues and there are environmental pressures which expect me to conform to the rat race of indian society. So, I figured that this was the best way to kill two birds with the same stone; I master my fundamentals as well as create the foundation for my real life later on. I won't give up on my idea though and I try to force stuff through my head at each sane moment of time I get. Any suggestions? Thank you for commenting.
- dododo 16y ago
  often the simplest things in machine learning/data mining work best---so maybe come up with a very simple way of achieving what you want, try it out. work out what's not so good, and improve. repeat. an important thing is to work out what maths you can just rationalise and ignore the details of, and what maths you need to know in detail. for example, you probably at this stage don't need to know how to prove the central limit theorem, but it might help you to know the intuition. it might be a good idea to know, in detail, where linear regression comes from though. warning: in my experience, data mining books tend to provide poor explanations of the mathematical justifications of what's going on. if you can, get to a library and get some more theoretical books on machine learning or statistics. in stats, larry wasserman's all of statistics is great, in machine learning, hastie et al's the elements of statistical learning, mackay's information theory book, bishop's machine learning book, etc, etc... with any text book, don't read them cover to cover. just get what you need and move on. if it's not obvious what you need from the book, try another one and go back. books can be expensive, but time is more precious. it's more important to do math than read math.

by dododo 16y ago

thesnark 16y ago

I agree with this. For me, math started to make sense when I saw it applied to problems, especially simple physics problems that explain things you can directly observe. The Feynman lectures were an especially rich source of these types of problems. My favorites: at what angle will a marble rolling down the side of a bowling ball leave the surface? when you observe water flowing out of your tap, the stream tappers and becomes more thin as it falls, can you derive the formula for that?

todayiamme 16y ago

Awesome. You nailed how I wanted to approach it. I am sorry if this comment sounds like a bunch of gibberish, but I am half asleep down here. I actually want to learn maths because I want to make this beautiful thing I have in my head. It's basically a user friendly data mining app that learns as you go along and it gives you the stuff you need. Not what I think you need. Basically I am trying to make a system that can collect data, and analyze it for someone who doesn't know what parameters to set in the first place. After that I want to apply what I learn from those interaction to trim the excess fat or give anything more if required. I know that this is a really lofty goal, but if I make it then I would be the happiest person on earth. As this is a part of an even bigger thing I want to make, which is brewing in my head. :) I haven't been able to get much mileage as I have concentration issues and there are environmental pressures which expect me to conform to the rat race of indian society. So, I figured that this was the best way to kill two birds with the same stone; I master my fundamentals as well as create the foundation for my real life later on. I won't give up on my idea though and I try to force stuff through my head at each sane moment of time I get. Any suggestions? Thank you for commenting.

dododo 16y ago
often the simplest things in machine learning/data mining work best---so maybe come up with a very simple way of achieving what you want, try it out. work out what's not so good, and improve. repeat. an important thing is to work out what maths you can just rationalise and ignore the details of, and what maths you need to know in detail. for example, you probably at this stage don't need to know how to prove the central limit theorem, but it might help you to know the intuition. it might be a good idea to know, in detail, where linear regression comes from though. warning: in my experience, data mining books tend to provide poor explanations of the mathematical justifications of what's going on. if you can, get to a library and get some more theoretical books on machine learning or statistics. in stats, larry wasserman's all of statistics is great, in machine learning, hastie et al's the elements of statistical learning, mackay's information theory book, bishop's machine learning book, etc, etc... with any text book, don't read them cover to cover. just get what you need and move on. if it's not obvious what you need from the book, try another one and go back. books can be expensive, but time is more precious. it's more important to do math than read math.