Machine learning, a branch of artificial intelligence, is a scientific discipline concerned with the development of algorithms that take as input empirical data, such as that from sensors or databases. The algorithm is designed to (a) identify (i.e., quantify) complex relationships thought to be features of the underlying mechanism that generated the data, and (b) employ these identified patterns to make predictions based on new data. Data can be seen as instances of the possible relations between observed variables; the algorithm acts as a machine learner which studies a portion of the observed data (called examples of the data or training data) to capture characteristics of interest of the data's unknown underlying probability distribution, and employs the knowledge it has learned to make intelligent decisions based on new input data.
One fundamental difficulty is that the set of all possible behaviors given all possible inputs is (in most cases of practical interest) too large to be included in the set of observed examples. Hence the learner must generalize from the given examples in order to produce a useful output from new data inputs.
Optical character recognition, in which printed characters are recognized automatically based on previous examples, is a classic engineering example of machine learning.
Read more about Machine Learning: Definition, Generalization, Machine Learning, Knowledge Discovery in Databases (KDD) and Data Mining, Human Interaction, Algorithm Types, Theory, Applications, Software, Journals and Conferences
Famous quotes containing the words machine and/or learning:
“The cycle of the machine is now coming to an end. Man has learned much in the hard discipline and the shrewd, unflinching grasp of practical possibilities that the machine has provided in the last three centuries: but we can no more continue to live in the world of the machine than we could live successfully on the barren surface of the moon.”
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“The value of a family is that it cushions and protects while the individual is learning ways of coping. And a supportive social system provides the same kind of cushioning for the family as a whole.”
—Michael W. Yogman, and T. Berry Brazelton (20th century)