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一、什麼是機器學習
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1.Arthur Samuel提出的定義：
“The field of study that gives computers the ability to learn without being explicitly programmed.”
2.Tom Mitchell提出的定義：
“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.”
二、監督學習
In supervised learning, we are given a data set and already know what our correct output should look like, having the idea that there is a relationship between the input and the output.
監督學習的問題被分爲“迴歸(regression)”和“分類(classification)”兩類。
1、在迴歸問題中，我們嘗試預測出連續的輸出。換句話說，我們是嘗試將變量映射到某一個連續函數上。
2、在分類問題中，我們嘗試預測出離散的輸出。換句話說，我們是嘗試將變量映射到某一些離散分類裏。
三、無監督學習
Unsupervised learning, allows us to approach problems with little or no idea what our results should look like. We can derive structure from data where we don’t necessarily know the effect of the variables.
無監督學習，使我們能夠處理那些對結果瞭解甚少、甚至根本不瞭解的問題。我們可以在不知道變量的具體影響的情況下，從數據中提取出結構（structure）。無監督學習不能從預測的結果中得到反饋（沒有性能測度），也就是說，沒有老師來糾正你。
我們可以根據數據中的變量關係對數據進行聚類（clustering），來提取出數據的結構。