What are the differences between types of Machine Learning?

Machine learning can be broadly classified into three types: supervised learning, unsupervised learning, and reinforcement learning. In supervised learning, labeled data is used to train the model to predict or classify new data accurately. Unsupervised learning, on the other hand, does not have labeled data, and the model has to find relationships among the input data itself. Reinforcement learning is a type of unsupervised learning where an agent learns to make decisions by interacting with an environment and receiving rewards or penalties. Each type of machine learning has its own advantages and disadvantages, and choosing the appropriate type depends on the task at hand.

This mind map was published on 3 June 2023 and has been viewed 129 times.