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There are different ways of how a machine learns. In some cases, we train them and, in some other cases, machines learn on their own. Well, primarily, there are two types of machine learning – Supervised Learning and Unsupervised Learning. In this module, we are going to discuss the types of machine learning in detail.
The type of learning algorithm where the input and the desired output are provided is known as the Supervised Learning Algorithm. In Supervised Machine Learning, labeled data is used to train machines in order to make them learn and establish relationships between given inputs and outputs.
Now, you must be wondering what labeled data means, right? Well, a label is nothing but a known description or a tag given to objects in the data. For instance, you have a dataset that consists of information related to 10 different patients with respective symptoms and their cancer test results. Based on the test results, you can put a tag on each patient specifying whether they are cancer positive or cancer negative.