Machine learning refers to the process of comprehending the patterns present in a dataset. It helps machines to learn from any given data and produce appropriate results, without being programmed explicitly. Basically, machine learning algorithms are fed with large amounts of data that they can work on and build a model. This model is later used by businesses to generate solutions that help them with analysis and building strategies for the future.
Machine learning is further categorized into unsupervised and supervised learning. Let's understand these in detail in the next section.
Unsupervised learning is the method by which algorithms tend to learn patterns within data that is not labeled. Since labels (supervisors) are absent, it is referred to as unsupervised learning. In unsupervised learning, you provide the algorithm with the feature data and it learns patterns from the data on its own.
Unsupervised learning is further...