[Machine Learning (Andrew NG courses)]I. Introduction

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1.What is machine learning?

       Machine learning is the field of study that gives computers the ability to learn without being explicitly programmed.

     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. 

2.Differences betweent classification and  regression problem

    Classification is appropriate when we are trying to predict one of a small number ofdiscrete-valued outputs, such as whether it will rain (which we might designate as class 0), or not (say class 1). (少量离散值)

     Regression is appropriate when we are trying to predict a continuous-valued output. Even though the number of shares traded is technically discrete-valued (i.e., an integer), it would be more natural to treat it as a continuous value (similar to the housing prices example in the lecture).（大量离散值，连续值）

2.Differences betweent Supervised Learning and Unsupervised Learning

   Supervised learning "right answers" given. eg:对于房价预测问题，数据中的每个数据，每个面积的房价已给出，预测更多房价。

    训练集中的每个数据都有正确答案。算法基于那些数据做出判断。

    无监督学习(unsupervised learning):设计分类器时候，用于处理未被分类标记的样本集

[Machine Learning (Andrew NG courses)]I. Introduction

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原文地址：http://blog.csdn.net/zqh_1991/article/details/39899687