Differentiate between supervised and unsupervised machine learning?

Question

Accepted Answer

Supervised learning uses labeled data to train models while unsupervised learning uses unlabeled data.

Supervised learning requires a target variable to be predicted while unsupervised learning does not.
Supervised learning algorithms include regression, classification, and decision trees while unsupervised learning algorithms include clustering and association.
Examples of supervised learning include predicting housing prices and classifying emails as spam or not, while examples of unsupervised learning include customer segmentation and anomaly detection.

Accepted Answer

Supervis machine learning relies on labelled input and output training data whereas unsupervised learning processes unlabelled Or raw data in supervised machine learning the model learns the 
relationship between the labelled input and output data

Accepted Answer

Supervised learning algorithms are trained using labeled data.

Unsupervised learning algorithms are trained using unlabeled data.

Accepted Answer

In supervised machine learning, the machine is trained using labeled data.                                     In unsupervised machine learning the machines are not trained using data, the algorthims makes decisions with out any corresponding output value.

Differentiate between supervised and unsupervised machine learning?

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