there are many algorithem available in machine learning. It works on the bases of the algorithm such as Supervised learning, Unsupervised learning, Semisupervised learning, Reinforcement learning etc
supervised learning:-It is used to develop the predicate model based on both inputs and desired output data. It has two way to develop predictive models.
• Classification techniques.
• Regression techniques.
Unsupervised learning:-It is used to develop a predicate model based on only input and it helps to find hidden patterns or intrinsic structure in data and it works on the base of k-means, hierarchical clustering, Gaussian mixture model these algorithms commonly used in unsupervised learning.
Semisupervised learning:- It works in between supervised and unsupervised learning. It uses both labeled and unlabeled data for training, typically a small amount of labeled data and a large amount of unlabeled data.
Reinforcement learning:-It is a method that interacts with its environment by producing actions and discovers errors.