机器学习
下面是Arthur Samuel(1959)的定义：
Field of study that gives computers the ability to learn without being explicitly programmed.
在没有明确设置的前提下，是计算机具有学习能力的研究领域。
机器学习与人的学习的区别在于，机器没有情绪，有强大的时间和空间，去做大量的测试，因此计算机有时候比人类自己更能拥有去做某一件事情的能力。
下面是Tom Mitchell(1998)的定义：
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.
计算机程序从经验E中学习，解决某一任务T进行某一性能度量P，通过P测定在T上的表现因经验E而提高。
Suppose your email program watches which emails you do or do not mark as spam, and based on that learns how to better filter spam. What is the task T in this setting?
- Classifying emails as spam or not spam.
- Watching you label emails as spam or not spam.
- The number (or fraction) of emails correctly classified as spam/not spam.
- None of the above - this is not a machine learning problem.
answer：
Classifying emails as spam or not spam.
performance E：
Watching you label emails as spam or not spam.
performance measure P:
The number (or fraction) of emails correctly classified as spam/not spam.
Machine learning algorithms:
- Supervised learning （监督学习）：我们教计算机做某件事情
- Unsupervised learning（无监督学习）：我们让计算机自己学习
