Machine learning and data mining are both ways that computers learn from data. It's like how you learn from things that happen around you. Let's say you're learning to ride a bike. You try it out, and if you fall off, you adjust what you did wrong and try again. Machine learning and data mining work in a similar way. They look at a lot of data and try to find patterns and connections between things. The computer then uses what it learned to make predictions or decisions about new data.
The difference between machine learning and data mining is like the difference between riding a bike and exploring a new place. Machine learning is when the computer is trying to learn from data and make predictions or decisions based on what it learned. It's like you riding a bike and trying to get better at it. Data mining, on the other hand, is when the computer is trying to find patterns and connections in data, but it's not necessarily trying to make any predictions or decisions based on what it finds. It's like exploring a new place and trying to understand how things are connected.
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