Machine Learning Note Introduction Introduction What is Machine Learning? Two definitions of Machine Learning are offered. Arthur Samuel described it as:"the filed of study that gives computers the ability to learn without being explicitly programmed…

Machine Learning 这是第一份机器学习笔记,创建于2019年7月26日,完成于2019年8月2日. 该笔记包括如下部分: 引言(Introduction) 单变量线性回归(Linear Regression with One Variable) 线性代数(Linear Algebra) 多变量线性回归(Linear Regression with Multiple Variables) Octave 逻辑回归(Logistic Regression) 正则化(Regularizat…

I am working on the Andrew Ng's course on Machine Learing. I have a question on the week2 session. Is there anybody can tell me why there is a 1/2m in front of the cost function.…

[Andrew Ng NIPS2016演讲]<Nuts and Bolts of Applying Deep Learning (Andrew Ng) 中文详解:https://mp.weixin.qq.com/s/ZbUCh5bi6Ech55qJR2gaxg…

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…

Here is the note for lecture three. the linear model Linear model is a basic and important model in machine learning. 1. input representation     The data we get usually needs some changes, most of them is the input data.      In linear model,       …

Python开发工具:Anaconda+Sublime 作者:白宁超 2016年12月23日21:24:51 摘要:随着机器学习和深度学习的热潮,各种图书层出不穷.然而多数是基础理论知识介绍,缺乏实现的深入理解.本系列文章是作者结合视频学习和书籍基础的笔记所得.本系列文章将采用理论结合实践方式编写.首先介绍机器学习和深度学习的范畴,然后介绍关于训练集.测试集等介绍.接着分别介绍机器学习常用算法,分别是监督学习之分类(决策树.临近取样.支持向量机.神经网络算法)监督学习之回归(线性回归.非线性回归…

1. scikit-learn介绍 scikit-learn是Python的一个开源机器学习模块,它建立在NumPy,SciPy和matplotlib模块之上.值得一提的是,scikit-learn最先是由David Cournapeau在2007年发起的一个Google Summer of Code项目,从那时起这个项目就已经拥有很多的贡献者了,而且该项目目前为止也是由一个志愿者团队在维护着. scikit-learn最大的特点就是,为用户提供各种机器学习算法接口,可以让用户简单.高效地进行数…

In recent years, Kernel methods have received major attention, particularly due to the increased popularity of the Support Vector Machines. Kernel functions can be used in many applications as they provide a simple bridge from linearity to non-linear…

Machine Learning Algorithms Study Notes 高雪松 @雪松Cedro Microsoft MVP 本系列文章是Andrew Ng 在斯坦福的机器学习课程 CS 229 的学习笔记. Machine Learning Algorithms Study Notes 系列文章介绍 2    Supervised Learning    3 2.1    Perceptron Learning Algorithm (PLA)    3 2.1.1    PLA --…

    Graph-powered Machine Learning at Google     Thursday, October 06, 2016 Posted by Sujith Ravi, Staff Research Scientist, Google ResearchRecently, there have been significant advances in Machine Learning that enable computer systems to solve compl…

from:http://analyticsbot.ml/2016/10/machine-learning-pre-processing-features/ Machine Learning : Pre-processing features October 21, 2016 I am participating in this Kaggle competition. It is a prediction problem contest. The problem statement is: How…

https://jmetzen.github.io/2015-01-29/ml_advice.html Advice for applying Machine Learning This post is based on a tutorial given in a machine learning course at University of Bremen. It summarizes some recommendations on how to get started with machin…

Machine Learning Methods: Decision trees and forests This post contains our crib notes on the basics of decision trees and forests. We first discuss the construction of individual trees, and then introduce random and boosted forests. We also discuss…

A Gentle Introduction to the Gradient Boosting Algorithm for Machine Learning by Jason Brownlee on September 9, 2016 in XGBoost 0 0 0 0   Gradient boosting is one of the most powerful techniques for building predictive models. In this post you will d…

Teaching Your Computer To Play Super Mario Bros. – A Fork of the Google DeepMind Atari Machine Learning Project Posted by ehrenbrav on August 25, 2016Leave a comment (14)Go to comments   For those who want to get right to the good stuff, the installa…

Machine Learning for Developers Most developers these days have heard of machine learning, but when trying to find an 'easy' way into this technique, most people find themselves getting scared off by the abstractness of the concept of Machine Learnin…

Decision Boundaries for Deep Learning and other Machine Learning classifiers H2O, one of the leading deep learning framework in python, is now available in R. We will show how to get started with H2O, its working, plotting of decision boundaries and…

17 Great Machine Learning Libraries 08 October 2013 After wonderful feedback on my previous post on Scikit-learn from the guys at /r/MachineLearning, I decided to collect the list of machine learning libraries into this seperate note. Let me know if…

Seven Steps to Success Machine Learning in Practice Project failures in IT are all too common. The risks are higher if you are adopting a new technology that is unfamiliar to your organisation. Machine learning has been around for a long time in acad…

In machine learning, is more data always better than better algorithms? No. There are times when more data helps, there are times when it doesn't. Probably one of the most famous quotes defending the power of data is that of Google's Research Directo…

Machine Learning Lab1 打算把Andrew Ng教授的#Machine Learning#相关的6个实验一一实现了贴出来- 预计时间长度战线会拉的比較长(毕竟JOS的7级浮屠还没搞定.) ----------------------------------------------------------------------------------------------------------------------------------- 实验内容: 线性拟合 实验材…

Everything You Wanted to Know About Machine Learning 翻译了理解机器学习的10个重要的观点,增加了自己的理解.这些原则在大部分情况下或许是这样,可是详细问题详细分析才是王道,不加思索的应用仅仅能是一知半解. 所以张小龙才说'我说的都是错的'. note by 王犇 1. How Does Machine Learning Work? 一般来说机器学习算法做这三件事情来建立模型: A set of possible models to look…

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…

<Machine Learning>系列学习笔记 第一周 第一部分 Introduction The definition of machine learning (1)older, informal definition--Arthur Samuel--"the field of study that gives computers the ability to learn without being explicitly programmed." (2)modern d…

In my last article, I stated that for practitioners (as opposed to theorists), the real prerequisite for machine learning is data analysis, not math. One of the main reasons for making this statement, is that data scientists spend an inordinate amoun…

Machine learning is a branch in computer science that studies the design of algorithms that can learn. Typical machine learning tasks are concept learning, function learning or “predictive modeling”, clustering and finding predictive patterns. These…

http://blog.csdn.net/pipisorry/article/details/44783647 机器学习Machine Learning - Andrew NG courses学习笔记 Anomaly Detection异常检測 Problem Motivation问题的动机 Anomaly detection example Applycation of anomaly detection Note:for Frauddetection: users behavior exam…

##机器学习(Machine Learning)&深度学习(Deep Learning)资料(Chapter 2)---#####注:机器学习资料[篇目一](https://github.com/ty4z2008/Qix/blob/master/dl.md)共500条,[篇目二](https://github.com/ty4z2008/Qix/blob/master/dl2.md)开始更新------#####希望转载的朋友**一定要保留原文链接**,因为这个项目还在继续也在不定期更新．希望看到…

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…