Differences between supervised learning and unsupervised learning in machine learning

S.No.	Supervised learning	Unsupervised learning
1.	Knowledge of output learning with the presence of an expert.	No knowledge of output classes

2.	Data is labeled with a class or value	Data is unlabelled or value unknown.
3.	Its goal is to predict class of value label.	Its goal is to determine data patterns.
4.	Examples- Neural network, SVN decision tree, Bayesian classifiers, etc.	Examples- k-means, genetic algorithms, clustering approaches, etc.