What is machine learning?
machine learning : experience—->skill
The skill is something which can improve the performance of program
Why use machine learning
For example,how to recognize a tree？
One way is that,we may write down many rules of the tree(the rules can be so many),once we need to judge a object whether tree or not we can use these rules to determine.But in fact ,we didn’t recongize by this way.Just think how a three-year-old baby do this.They can recongnize the tree after seen a lot of tree,they don’t need to write down rules.Because they have seen too many tree so when they meet a new thing they can determine whether it is a really tree.
PC can recognize a tree like a three-years-old baby,they just need some data to deal with just like to see many trees like for training.And it would be more effective than writing rules.
What fileds can machine learning apply to?
For example,some interesting field
Navigating on Mars: we can not make rules in advance for the reason that we haven’t reach Mars before,we need machine to collect data and use these data to maker decision when it arrive to Mars
Speech/visual recognition: the feature of voice and image is hard to catch, it also means makeing rules is difficlut so it’s better to use machine
High-frequency trading marketing: it’s hard for human beings to make decision in only just seconds in trading market but marchine learning can do it.The program just need to be trained by the data earlier in the trading market and it would make decision for the later quickly.
Consumer-targeted marketing : make service for people in a large scale in the case the service is targeted,we can’t do it by artificial method,we need use machine learning
What problems is suitable for machine learning
There are three keys which would determine whether a problem fit to machine learning:
(1)Exists some underlying pattern to be bearning
(2)It’s hard to definite rule
(3)There should be a certain amount of data
What’s the aim of machine learning?
We have some input:x and some output:y==>(x,y)
There exists a underlying function f which make f(x)=y,but we don’t know the function f
So we should find hypothesis g : g f,there could be many function g ,but we need to chose the best one
What is the difference between machine learning,data mining,artical intelligence and statistics?
Machine learning: use data to compute hypothesis g targeted f
Data mining: use huge data to find property that is interesting, when the interesting property is hypothesis ,data mining ==machine learning
Artificical Intelligence : compute something that shows intelligent behavior,machine learning can relaize AI
Statistics :use data to make inferenceabout unknown process,traditionaly statistics values useing math provable result ,but machine learning puts highlight on computing data.Statistics can be used to realize ML,provides tools for ML