Unsupervised learning refers to data science approaches that involve learning without a prior knowledge about the classification of sample data. In Wikipedia, unsupervised learning has been described as "the task of inferring a function to describe h…

(Deep) Neural Networks (Deep Learning) , NLP and Text Mining 最近翻了一下关于Deep Learning 或者 普通的Neural Network在NLP以及Text Mining方面应用的文章,包括Word2Vec等,然后将key idea提取出来罗列在了一起,有兴趣的可以下载看看: http://pan.baidu.com/s/1sjNQEfz 我没有把一些我自己的想法放到里面,大家各抒己见,多多交流. 下面简单概括一些其中的几篇p…

Problems[show] Classification Clustering Regression Anomaly detection Association rules Reinforcement learning Structured prediction Feature engineering Feature learning Online learning Semi-supervised learning Unsupervised learning Learning to rank…

1    Unsupervised Learning 1.1    k-means clustering algorithm 1.1.1    算法思想 1.1.2    k-means的不足之处 1.1.3    如何选择K值 1.1.4    Spark MLlib 实现 k-means 算法 1.2    Mixture of Gaussians and the EM algorithm 1.3    The EM Algorithm 1.4    Principal Components…

Machine Learning and Data Mining Lecture 1 1. The learning problem - Outline     1.1 Example of machine learning Predicting how a viewer will rate a moive? 10% improvement = 1 million dollar prize The essence of machine learning: A pattern exists We…

Text mining is the application of natural language processing techniques and analytical methods to text data in order to derive relevant information. Text mining is getting a lot attention these last years, due to an exponential increase in digital t…

在进行文本挖掘时,TSQL中的通配符(Wildchar)显得功能不足,这时,使用“CLR+正则表达式”是非常不错的选择,正则表达式看似非常复杂,但,万变不离其宗,熟练掌握正则表达式的元数据,就能熟练和灵活使用正则表达式完成复杂的Text Mining工作. 一,正则表达式的特殊字符 1,常用元字符 用以匹配特定的字符(字母,数字,符号),注意字母是区分大小写的: . :匹配除换行符以外的任意字符 \w :匹配字母或数字或下划线或汉字 \s :匹配任意的空白符 \d :匹配数字 \b :匹配单词的…

一.课程简介: text mining and analytics 是一门在coursera上的公开课,由美国伊利诺伊大学香槟分校(UIUC)计算机系教授 chengxiang zhai 讲授,公开课链接:https://class.coursera.org/textanalytics-001/wiki/view?page=Programming_Assignments_Overview. 二.课程大纲: 三.课程主要内容 3.1 Text representation 可以从以下几个方面来对文…

Unsupervised Learning: Use Cases Contents Visualization K-Means Clustering Transfer Learning K-Nearest Neighbors The features learned by deep neural networks can be used for the purposes of classification, clustering and regression. Neural nets are s…

Supervised Learning 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…