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.


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