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.
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.
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.