Data Mining vs Machine Learning
Data Mining Vs Machine Learning
| Factors | Data Mining | Machine Learning |
|---|---|---|
| Origin | Traditional databases with unstructured data. | It has an existing algorithm and data. |
| Meaning | Extracting information from a huge amount of data. | Introduce new Information from data as well as previous experience. |
| Implementation | We can develop our own models where we can use data mining techniques for. |
We can use machine learning algorithm in the decision tree, neural networks and some other area of artificial intelligence. |
| History | In 1930, It was known as knowledge discovery in databases(KDD). |
The first program, i.e., Samuel's checker playing program, was established in 1950. |
| Responsibility | Data Mining is used to obtain the rules from the existing data. |
Machine learning teaches the computer, how to learn and comprehend the rules. |
| Abstraction | Data mining abstract from the data warehouse. | Machine learning reads machine. |
| Applications | When compared to machine learning, data mining can produce outcomes on the lesser volume of data. It is also used in cluster analysis. |
It has various applications, used in web search, spam filter, credit scoring, computer design, etc. |
| Nature | It has human interference more towards the manual. | It is automated, once designed and implemented, there is no need for human effort. |
| Techniques involve | Data mining is more of research using a technique like a machine learning. |
It is a self-learned and train system to do the task precisely. |
| Scope | Applied in the limited fields. | It can be utilized in a vast area. |