Two definitions of Machine Learning

Arthur Samuels in 1959 described machine learning as the field of study that gives computers the ability to learn without being explicitly programmed.

Tom Mitchell of Carnegie Mellon, in 1998, described machine learning as a “well-posed learning problem,” in which a computer program is said to learn from experience E with respect to some task T and some performance measure P, if its performance on T, as measured by P, improves with experience E.

Source: Andrew Ng, Machine Learning class on Coursera

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