In 1959, Arthur Samuel defined Machine Learning as: “Field of study that gives computers the ability to learn without being explicitly programmed.
More recently, in 1998, Tom Mitchell provided a well posed learning problem: 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.
There are multiple ways to describe this, however, Andrew Ng’s example of playing checkers is as follows:
E = the experience of playing many games of checkers;
T = the task of playing checkers;
P = the probability that the program will win the next game.
Machine learning problems can be assigned to two broad classifications
Applying machine learning as a data analytical technique, will help you proactively make better decisions from large amounts of data and lots of variables to consider. Machine Learning uses specific algorithms to detect patterns in the data, generate insights and make better predictions for your business.
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