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Machine Learning - Andrew Ng - Coursera Contents 1 Notes 1 Notes What is Machine Learning? Two definitions of Machine Learning are offered. Arthur Samuel described it as: "the field of study that gives computers the ability to learn without being exp…
Week1: Machine Learning: 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. Supervised Learning:We alr…
Week 1: Machine Learning: 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. Supervised Learning:We al…
Week 1 的内容主要有: 机器学习的定义 监督式学习和无监督式学习 线性回归和成本函数 梯度下降算法 线性代数回归 主要是了解一下机器学习的基本概念,重点是学习线性回归模型,以及对应的成本函数和梯度下降算法. 以上两幅图基本上就是week 1 的重点了. 下文是我做的比较粗糙的一个关于week 1 的总结.其中线性代数部分就省略掉了,大学里基本都有学过矩阵相关的操作.…
1.监督学习(supervised learning)&非监督学习(unsupervised learning) 监督学习:处理具有若干属性且返回值不同的对象.分为回归型和分类型:回归型的返回值是连续的,分类型的返回值是离散的. 非监督学习:将具有若干属性的相同对象分为不同的群体. 2.线性回归模型(监督学习) 2.1 一些符号 m——训练样本数目 x——输入变量 y——输出变量 (x,y)——一个训练样本 (x(i),y(i))——第i个训练样本 h——假设(hypothesis)——预测函数…
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https://www.quora.com/How-do-I-learn-machine-learning-1?redirected_qid=6578644   How Can I Learn X? Learning Machine Learning Learning About Computer Science Educational Resources Advice Artificial Intelligence How-to Question Learning New Things Lea…
http://blog.csdn.net/pipisorry/article/details/44119187 机器学习Machine Learning - Andrew NG courses学习笔记 Machine Learning System Design机器学习系统设计 Prioritizing What to Work On优先考虑做什么 the first decision we must make is how do we want to represent x, that is…
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