To me, both look the same. Both are used to find patterns in data or to learn something from it so where’s the difference?
In: Technology
Data mining is trying to understand how human work to predict their action. It’s using information gathered about people to try and understand the pattern so you can make advertisment that will work better. Example: By looking at people’s browser history, they realize that people that buy a lot of beer on a day before a big football match also usually buy charcoal and meat. So they decide to make a “barbecue” package when a big football match is coming.
Machine learning is a program learning from its mistake. The program tries to do something, fail then try to change its approach. try again, fail again, change approach. Try again, fail again, change approach. Try again, succeed for once, expand on this method. Try again using previous method but slightly tweaked, no longer work, tweak differently. Repeat, repeat, repeat. It’s doing the (almost) same thing over and over and over and over again observing things changing. Pick what works best and try to see if that idea can be tweaked to do better. Rinse and repeat.
Data mining is searching for similarities to somewhat predict the future (mostly used to predict people buying pattern)
Machine learning is letting a program learn for itself how best do a job.
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