Definition of ML 机器学习定义
定义1
the field of study that gives computers the ability to learn without being explicitly programmed." This is an older, informal definition.（Arthur Samuel）
定义2
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.（Tom Mitchell）
一个程序可以通过从经验E里学习，通过P检测，得到一个解决问题T更好的方法。
two Machine Learning Problem
Supervised Learning(监督学习)
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.
我们得到一个数据集，里面已经有了部分输入输出的关系，通过这个已知输入输出关系去预测我们任意的一个输入对应的输出。
分类
Regression（回归问题）
predict continuous output value(price)
Classification(分类问题)
通过已有数据集把数据分为几类
Unsupervised Learning(非监督学习)
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.
训练样本数据没有标记信息等，也不会给出目标的输出
分类
Clustering
Take a collection of 1,000,000 different genes, and find a way to automatically group these genes into groups that are somehow similar or related by different variables, such as lifespan, location, roles, and so on.
Unclustering
The “Cocktail Party Algorithm”, allows you to find structure in a chaotic environment. (i.e. identifying individual voices and music from a mesh of sounds at a cocktail party).