• In supervised machine learning, the machine is trained using labeled data. Then a new dataset is given into the learning model so that the algorithm provides a positive outcome by analyzing the labeled data. For example, we first require to label the data which is necessary to train the model while performing classification.
• In the unsupervised machine learning, the machine is not trained using labeled data and let the algorithms make the decisions without any corresponding output variables.