What is the difference between data mining and machine learning?

Data mining and machine learning are related fields, but they have different purposes:

• The goal of machine learning is to develop algorithms that allow computers to learn without human intervention. It’s about making machines smarter, so they can carry out tasks related to human intelligence independently.
• The goal of data mining is to sift through large data sets and extract useful information like patterns and relationships that can be used to support decision-making. In other words, it’s a tool for humans.

While data mining and machine learning have distinct goals, there is some overlap in their applications. Machine learning can be used as a means to conduct data mining by automatically detecting patterns in data. On the other hand, data gathered from data mining can be used to teach machines and improve their learning capabilities.

In short, data mining and machine learning can complement each other, but they are distinct in their purposes and applications.