supervised learning is that where we know input and output but don't know the processing

whereas unsupervised learning is that where we know input but don't know output ,we put our best effort for best processing

Machine Learning can be supervised, unsupervised, semi-supervised, or reinforced. From the supervised algorithms, some of the common methods include Naive bayes classifiers and Support Vector Machines. Unsupervised learning includes k-means and hierarchical clustering.

Classification is a type of supervised learning (Background knowledge is known) and Clustering is a type of unsupervised learning(No such knowledge is known).

idk thats why i am here

well , in supervised learning there must be a human (a teacher) to intervened , i.e. the desired response of the system is already known so the network is make the system to respond as the desired one. in unsupervised learning is the exact opposite of the supervised, in whichThe outputs are not known, so the network is allowed to settle into suitable states by discovering special features and patterning from available data without using an external help