These two terminologies are studied under the field of data science. Many people are confused to differentiate between them. They are often used interchangeably. They are sharing some common characteristics but they are quite different from each other in terms of their unique features and applications in the digital markets.
Difference between Data Mining and Machine Learning
What is Data Mining?
As the terminology of mining means the extraction so the data mining means that the extraction of information from vast amount of the data or from provided data. This is the technique used widely from different organizations. For better or convenient compilation of the large data, this technique is used to produce better outcomes.
This tool helps to find out the new knowledge and give uniform settings to the provided information or data. Data mining is unique due to its special functions as this technique helps in avoiding repetitive errors in the data.
This technique easily recognizes which tool is relevant and good for better outcomes by digging the required information from the data. It helps in making the right decisions by providing the right or accurate information from the data.
What is Machine Learning?
Machine learning is a branch of artificial intelligence. It is the method of analyzing the data. It is the branch of science that enables the computers to be act programmed implicitly. This system has the ability to learn from the past automatically without being programmed explicitly.
Machine Learning helps in accessing the data and learns from that data of the computer programs. The algorithms of machine learning have the ability to learn from past experiences and work more effectively. The target in machine learning is called a label. Those industries which have large amounts of data are using this software.
This software is basically built when computers are able to learn without being programmed for performing specific tasks.
Data Mining VS Machine Learning
Data mining and machine learning are different from each other while they have some commonalities. They are different in terms of their age as data mining was in use since 1930s and it is initially known as knowledge discovery in databases (KDD) and it is still known with this name while machine learning comes in the digital market since the 1950s.
This two software or techniques are also different regarding their purpose. The purpose of data mining is to extract the information while machine learning is to teach the computer how to learn and work from past experiences without programming.
Data mining is simply to researching and determining the particular outcomes which are based on the total gathered information. While the technique of machine learning is to train the system to work and perform complex tasks and used past experiences to perform well.
The other distinct thing which differentiates these two techniques from each other is their uses. Data mining is used when the organizations have vast stored data which helps in forecasting for business while machine learning is working only on algorithms not on raw data.