Supervised, semi-supervised, unsupervised, and reinforcement learning algorithms are the four categories of machine learning algorithms.

Types Description
Supervised Supervised learning, also called supervised machine learning, is a subdivision of machine learning and artificial intelligence. It is defined by using a labeled dataset to train an algorithm to classify data or accurately predict outcomes.
Semi-supervised It is a merger of supervised and unsupervised learning. Semi-supervised uses a small amount of labeled and a large amount of unlabeled data to provide the benefits of both unsupervised and supervised learning while avoiding the challenges of finding large amounts of labeled data.
Unsupervised It is also known as unsupervised machine learning, uses machine learning algorithms to analyze and group unlabeled datasets. These Unsupervised algorithms discover hidden patterns and groups in data without the need for human intervention.
Reinforcement It is scientific decision-making. It is about learning the optimal behavior within the environment for the greatest reward.
BY Best Interview Question ON 30 Dec 2023