udacity data mining

If you have a shopping website, how do you recommend products to your customers? This function is available on many e-commerce websites. You can easily build similar functions through the data mining feature of SQL Server Analysis Services. It is divided into three parts to demonstrate how to implement this function. 1. Build a Mining Model 2. Compile service in

independent and has no correlation.If that is less than 0, the description is negatively correlated, and one value increases by another.Note that correlations do not imply causality, and if A and B are relevant, it does not mean that a causes B or B to cause a.3. Covariance of numeric dataCovariance and variance are two similar measures that evaluate how the two properties change together. The mean values of A and B are also known as expectations.The covariance of A and B is defined as:　　　　For

ObjectiveThis article continues our Microsoft Mining Series algorithm Summary, the previous articles have been related to the main algorithm to do a detailed introduction, I for the convenience of display, specially organized a directory outline: Big Data era: Easy to learn Microsoft Data Mining algorithm summary seria

Common Data Mining MethodsBasic Concepts Data Mining is fromMassive, incomplete, noisy, and fuzzyThe process of extracting potentially useful information and knowledge hidden in the data that people do not know beforehand. Specifically, as a broad application-oriented cross-

From: http://www.how2dns.com/blog? P = 352 If you are familiar with Java, we often think of WEKA when thinking about data mining, and the data mining: Practical machine learning tools and techniques written by Ian H. Witten has a Chinese version, so there are many users. Recently, I want to use python to process

In various data mining algorithms, association rule mining is an important one, especially influenced by basket analysis. association rules are applied to many real businesses, this article makes a small Summary of association rule mining. First, like clustering algorithms, association rule

Ten classic algorithms in machine learning and Data Mining Background: In the early stage of the top 10 algorithm, Professor Wu made a report on the top 10 challenges of Data Mining in Hong Kong. After the meeting, a mainland professor put forward a similar idea. Professor Wu felt very good and began to solve the probl

Customer churn is a big problem facing banks in the increasingly competitive market. By analyzing the reasons of bank customer churn, this paper puts forward a method of establishing customer churn prediction model. By using the model, we find out the forecast loss group, forecast the loss trend, and then formulate effective control strategy to minimize the customer churn rate. It provides a new research idea and analysis method for customer churn prediction. [Key words] customer churn loss Pred

1 Introduction With the increasing popularity of the Internet, various forms of information generation and collection have led to the explosion. The competitive trend of modern society requires real-time and deep analysis of this information, although there is now a more powerful information storage and retrieval system. But users are becoming more and more difficult to analyze and use the information they have. How to effectively organize and utilize a large amount of information, so that user

Some people work very original, there are some very new things every year. Some people have a lot of articles, but mainly follow others ' work. There are many paper machine in the database field. In some places, the whole group is a big paper machine.Personal feeling database researchers tend to think of data mining as a sub-domain of a database, and thus have lower rating for

Data mining-detailed explanation of the Apriori algorithm and Python implementation code, aprioripython Association rule mining is one of the most active research methods in data mining, the earliest reason was to discover the relationship between different commodities in th

We do data analysis, data mining commonly used in the R language to deal with, and the use of good or bad often related to the proficiency of the function, the following we have a small series of Holy Sage Summary of the R language commonly used in the data frame of the basic operation. The concept of

PS: Due to space issues, this blog mainly introduces the project Understanding Problem in the data mining standardization process. The remaining five aspects are as follows, in particular, modeling and other components involving specific algorithms will be written in the follow-up blog in the form of open-source software such as orange and knime or some Python applets. Part of this article is translation, a

1. The data analysis (Douban) book is quite simple. The basic content is involved, and it is clear. Finally, we talked about R as a plus.Difficulty level: very easy.2. Beer and diapers (Douban) are the most typical cases.Difficulty level: very easy.3. The beauty of data (Douban) An introductory book, each chapter solves a specific problem, and even has code, which is very helpful for understanding the appli

Entry books: In-Depth Data Analysis (Douban)This book is quite simple. The basic content is involved, and it is quite clear. Finally, we talked about R as a plus. Difficulty level: very easy. Beer and diapers (Douban)In this case, things are the most typical examples. Difficulty level: very easy. Data beauty (Douban)Each chapter of an introductory book solves a specific problem and even contains code,

(written in front) said yesterday to write a machine learning book, then write one today. This book is mainly used for beginners, very basic, suitable for sophomore, junior to see the children, of course, if you are a senior or a senior senior not seen machine learning is also applicable. Whether it's studying intelligence or doing other things, machine learning is a must. You see GFW all use machine study, we also have to science.(full-text structure) In fact, I think, learn a subject, List a p

Preface 1The first part of social network guidancePrologue 13The 1th Chapter explores Twitter: Exploring hot topics, discovering what people are talking about, etc. 151.1 Overview 15Reasons for 1.2 Twitter rage 161.3 Explore Twitter API 181.4 Analysis of 140 word tweets 331.5 Summary of this chapter 471.6 Recommended Exercises 481.7 Resources Online 482nd Chapter Mining Facebook: Analyzing fan pages, viewing friends, etc. 502.1 Overview 512.2 Explore

More familiar with Matlab, use it relatively handy, feel Shffield Genetic algorithm Toolbox and Neural Network toolbox are very useful, and simple programming, debugging program is also easy, Python only learned some foundation, want to proficiency to MATLAB that degree still need a period of time, may be MATLAB spoiled, always feel python all kinds of uncomfortable ... Questions come, if you get rid of Python only with MATLAB can learn the knowledge of data