2018-05-25 Machine Learning by Andrew Ng

参考Andrew Ng 课程 Machine Learning

机器学习的定义：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.

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.

Supervised learning problems are categorized into "regression" and "classification" problems. 

In a regression problem, we are trying to predict results within a continuous output, meaning that we are trying to map input variables to some continuous function. 

In a classification problem, we are instead trying to predict results in a discrete output. In other words, we are trying to map input variables into discrete categories.

栗子。

(a) Regression - Given a picture of a person, we have to predict their age on the basis of the given picture

(b) Classification - Given a patient with a tumor, we have to predict whether the tumor is malignant or benign.

Unsupervised Learning(无监督学习):聚类／非聚类

一些符号的表示。

x(i) to denote the “input” variables

y^{(i)}y(i) to denote the “output” or target variable

i=1,...,m—is called a training set.

梯度下降的特点：从不同点出发，可能得到不同的局部最优解。

Prediction = DataMatrix * Parameters