Machine learning can be broadly classified into supervised and unsupervised learning. By definition, the term supervised means that the “machine” (the system) learns with the help of something—typically a labeled training data.
Training data (or a dataset) is the basis on which the system learns to infer. An example of this process is to show the system a set of images of cats and dogs with the corresponding labels of the images (the labels say whether the image is of a cat or a dog) and let the system decipher the features of cats and ...
