Difference Between Data Mining and Machine Learning

Parameter	Data Mining	Machine Learning
Definition	Data mining is a process to extract information from a data set and transform it into an understandable structure for further use.	It is a Technique that concerns the construction and study of systems that can learn from data.
Focus	It focuses on the discovery of unknown properties in the data.	It focuses on prediction, based on known properties learned from training data.
Database Size	It is an automatic or semi-automatic analysis that is performed on large quantities of data.	It is generally performed on small databases to increase accuracy.
Types	Association Rules Classification Clustering Sequential Patterns Sequence Similarity	Supervised Un Supervised Reinforcement
Relationship	Data Mining uses various Machine Learning methods, but for slightly different goals.	Machine learning also uses data mining Technique as "unsupervised learning" or as a “preprocessing step” for improvement of learner accuracy.
Applications	Forecasting Classifying Things Associating Similar Things Clustering into Groups Sequence Making	Automating  Employee Access Control Protecting Animals Predicting Emergency wait room times Identifying Heart Failure Classroom will learn, Digital Guardian, City will help you live in it and many more……
Example Software’s Used	Carrot2, GATE, UIMA, Weka, NLTK, Torch etc.	Apache Mahout ,ELKI, H2O, OpenCV, OpenNN, Weka, MATLAB etc.