IB Digital Society 3.6B Types and Uses of Machine Learning Key Definitions

A form of machine learning that uses artificial neural networks with many layers to learn complex patterns directly from large amounts of raw data, powering tasks such as image and speech recognition.

A machine learning application that identifies or verifies a person from an image or video by comparing patterns in their facial features against stored data.

A subset of artificial intelligence that enables systems to learn from data and improve their performance over time without explicit programming.

Computational models inspired by the human brain that use neurons to learn from data to perform tasks like classification, prediction, and pattern recognition.

A type of machine learning where an agent learns by trial and error in an environment, taking actions and adjusting its behaviour to maximise a reward signal over time.

A type of machine learning where a model is trained on labelled data, meaning each example is tagged with the correct answer, so it learns to predict the label for new, unseen inputs.

A type of machine learning where a model is given unlabelled data and finds patterns, groups, or structure in it on its own, without being told the right answers in advance.