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Machine Learning

muh-SHEEN LURN-ing /məˈʃiːn ˈlɜːrnɪŋ/

nounC1GRETOEFLIELTS

formaltechnical

A subset of Artificial Intelligence that enables systems to learn from data, identify patterns, and make decisions with minimal human intervention.

Machine Learning (ML) is characterized by its focus on algorithms that allow computers to improve their performance on a task over time, as they are exposed to more data, rather than being explicitly programmed for every possible scenario.

The story behind the word. The term 'Machine Learning' was coined by Arthur Samuel in 1959, an IBM pioneer in computer gaming and artificial intelligence. 'Machine' comes from the Latin `machina` (a device or engine), and 'learning' from the Old English `leornian` (to acquire knowledge). Samuel defined it as a 'field of study that gives computers the ability to learn without being explicitly programmed.'

Word relationships

statistical learning: Emphasizes the statistical foundations of many ML techniques.

Commonly confused with

Artificial Intelligence: Machine Learning is a specific approach within the broader field of Artificial Intelligence.
Deep Learning: Deep Learning is a specialized subfield of Machine Learning that uses multi-layered neural networks.

Word family

machine-learned (adjective): Acquired or developed through machine learning.

Collocations

Machine Learning algorithms
apply Machine Learning
Machine Learning model
Machine Learning engineer

Example sentences

"Netflix uses sophisticated Machine Learning algorithms to suggest movies and TV shows based on your viewing history." Explaining how recommendation systems work.
"The new diagnostic tool leverages Machine Learning to analyze medical images and detect early signs of disease with remarkable accuracy." Discussing a new development in healthcare.

Memory hook

Think of a 'machine' that 'learns' from examples, like a student studying a textbook. Machine Learns

When not to use

While all Machine Learning is AI, not all AI is Machine Learning. Avoid using ML when referring to broader AI concepts that don't involve learning from data (e.g., rule-based expert systems).

Fun facts

Arthur Samuel's checkers-playing program in the 1950s was one of the earliest examples of a machine learning system.
Machine learning is behind many everyday technologies, from spam filters to facial recognition.

Explore more words

algorithmic, analytics, conditioned, Predictive, Visualization