Machine learning builds a model based on training data. This does not require explicit knowledge represention of rules or facts, instead the algorithm creates its own representation. Some machine learning algorithms produce human-undertandable representations, such as decision trees, others, including neural networks are harder to interpret and may need explainable AI technques.
Machine learning typically progresses in three phases: training phase, validation phase and application phase.
Used in glossary entries: application phase, decision tree, explainable AI, neural network, training data, training phase, validation phase
Phases of machine learning