Machine Learning
Supervised Learning
Supervised Learning is essentially a method that teaches machines to learn the mapping relationship between inputs and outputs through correctly labeled data, aiming to train a model that can accurately predict new data.
Supervised Learning is primarily composed of regression and classification.
Classification is different from regression,classification tries to predict only a small number of possible outputs or categories rather regression tries to predict any number out of an infinitely many number of possible numbers.Classification differs from regression in that classification aims to predict a limited set of possible outputs or categories, while regression attempts to predict any value from an infinite range of possible numbers.
Unsupervised Learning
Clustering Algorithm
Unsupervised Learning groups some unlabeled data into clusters according to some underlying structure in the data.
