Welcome to MyBlog! This article was writed to take note my study of Machine Learning on Cousera.
什么是机器学习？（三要素，两分类）
在Cousera上，吴恩达的ml课程中是这样解释：
Tom Mitchell provides a more modern definition: “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.”
也就是说：一个计算机程序，根据任务T和绩效评估P，从经验E中学习。其中，程序在T中表现，由P评估，随经验E而改善。
举例：下棋
E = 下过很多盘棋的棋手的经验
T = 下棋的任务
P = 程序在下一盘棋中，获胜的概率
分类：
supervised learning(监督学习）, unsupervised learning（无监督学习）
Supervised Learning 监督学习
引用课程原话：
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.
有监督学习分为两种：回归问题和分类问题
举例：
回归Regression：给一张人物照片，根据照片判断人物的年龄 （连续的）
分类Classification：给一张人物照片，根据照片判断人物的性别 （离散的）
Unsupervised Learning 无监督学习
引用课程原文：
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.
We can derive this structure by clustering the data based on relationships among the variables in the data.
With unsupervised learning there is no feedback based on the prediction results.
举例：
聚类Clustering：收集100000个不同的基因，找一个方法，自动将这些基因分成几类，同一个类别的基因在某种程度上相似或者在其他方面有关联
原文：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.
非聚类Non-clustering：鸡尾酒聚会算法（Cocktail Party Algorithm），下面简单描述这个算法
在鸡尾酒聚会上，有很多声音，包括人声、背景音乐，通过这个算法，可以输出每个个体的声音。总之，就是从嘈杂的环境中找到有条理/有结构的东西。identifying individual voices and music from a mesh of sounds at a cocktail party
More info: Cousera - Machine Learning
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