What is Machine Learning?

Two definitions of Machine Learning are offered.

Arthur Samuel described it as: “the field of study that gives computers the ability to learn without being explicitly programmed.” This is an older, informal definition.
Tom Mitchell provides a more modern definition: “A computer program is said to learn from experience E with respect to some class of tasks T and performance measure P, if its performance at tasks in T, as measured by P, improves with experience E.”
“对于某类任务T 和性能度量 P，如果一个计算机程序在 T 上以 P 衡量的性能随着经验 E 而自我完善，那么我们称这个程序在经验 E 中学习”

Example: playing checkers.

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.

In general, any machine learning problem can be assigned to one of two broad classifications:

Supervised learning and Unsupervised learning.