Supervised Learning
Definition
Supervised learning is a type of machine learning where an algorithm learns from labeled data to make predictions.
In supervised learning, the training data consists of input-output pairs. The algorithm is provided with a set of examples where each input has a known correct output. The goal of the algorithm is to learn a mapping function from the input to the output, enabling it to predict the output for new, unseen inputs. This process is akin to a student learning with a teacher who provides correct answers for practice problems.
For instance, a model trained on images of cats and dogs, each labeled accordingly, can learn to identify whether a new, unlabeled image contains a cat or a dog.
Supervised learning is extensively employed in areas such as image recognition, spam filtering, medical diagnosis, and predictive maintenance.