GC: n

CT: Machine learning is the science of getting computers to act without being explicitly programmed. In the past decade, machine learning has given us self-driving cars, practical speech recognition, effective web search, and a vastly improved understanding of the human genome. Machine learning is so pervasive today that you probably use it dozens of times a day without knowing it. Many researchers also think it is the best way to make progress towards human-level AI.

S: https://www.coursera.org/course/ml (last access: 31 December 2014)

N: 1. – machine (n): 1540s, “structure of any kind,” from Middle French machine “device, contrivance,” from Latin machina “machine, engine, military machine; device, trick; instrument” (source also of Spanish máquina, Italian macchina), from Greek makhana, Doric variant of Attic mekhane “device,” from PIE *magh-ana- “that which enables,” from root *magh- “to be able, have power.”
– learning (n): Old English leornung “study, action of acquiring knowledge,” verbal noun from leornian. Meaning “knowledge acquired by systematic study, extensive literary and scientific culture” is from mid-14c. Learning curve attested by 1907.
2. The process by which a functional unit improves its performance by acquiring new knowledge or skills, or by reorganizing existing knowledge or skills.
3. Machine learning is a research effort that seeks to create computer programs that can learn from experience. Such programs, when they become available, will remove a major barrier to the development of a very large expert system.
4. machine learning; automatic learning: terms and definition standardized by ISO/IEC.
5. Also, a subdomain of artificial intelligence concerned with developing computational theories of learning and constructing machines with learning capabilities.
6. A common definition of Machine Learning concludes it is a scientific discipline concerned with the design and development of algorithms that allow machines (computers) to make decisions or even evolve behaviors based on collection of empirical data. There is a difference between AI (artificial intelligence) and machine learning, as the latter is a branch of AI. Empirical data can be collected from sensors and analyzed comparing existing databases. A major focus of machine learning research is to automatically learn to recognize patterns and make intelligent decisions based on data.

S: 1. OED – http://www.etymonline.com/index.php?allowed_in_frame=0&search=machine+learning (last access: 19 May 2017). 2 to 5. TERMIUM PLUS – http://goo.gl/NawTYF (last access: 31 December 2014). 6. http://www.academypublish.org/book/show/title/machine-learning (last access: 31 December 2014).

SYN: 1. ML. 2. automatic learning. 3. automated learning.

S: 1. GDT – http://www.granddictionnaire.com/ficheOqlf.aspx?Id_Fiche=8395061 (last access: 31 December 2014). 2. TERMIUM PLUS – http://goo.gl/NawTYF (last access: 31 December 2014); GDT – http://www.granddictionnaire.com/ficheOqlf.aspx?Id_Fiche=8395061 (last access: 31 December 2014). 3. TERMIUM PLUS – http://goo.gl/NawTYF (last access: 31 December 2014).

CR: artificial intelligence, computational intelligence, computer science, deep learning, e-learning, virtual personal assistant.