数据挖掘和机器学习的区别

数据挖掘：
从海量数据中提取有用信息的过程称为数据挖掘。数据挖掘是人类用来发现新的、准确的和有用的数据模式或为需要它的人提供有意义的相关信息的工具。

机器学习：
发现改进了经验派生数据的算法的过程称为机器学习。正是这种算法允许机器在没有人工干预的情况下学习。它是一种使机器更智能、消除人为因素的工具。

下表列出了数据挖掘和机器学习之间的差异：

S.No.	Data Mining	Machine Learning
1.	Extracting useful information from large amount of data	Introduce algorithm from data as well as from past experience
2.	Used to understand the data flow	Teaches the computer to learn and understand from the data flow
3.	Huge databases with unstructured data	Existing data as well as algorithms
4.	Models can be developed for using data mining technique	machine learning algorithm can be used in the decision tree, neural networks and some other area of artificial intelligence
5.	human interference is more in it.	No human effort required after design
6.	It is used in cluster analysis	It is used in web Search, spam filter, fraud detection and computer design
7.	Data mining abstract from the data warehouse	Machine learning reads machine
8.	Data mining is more of a research using methods like machine learning	Self learned and trains system to do the intelligent task
9.	Applied in limited area	Can be used in vast area