Alibabacloud.com offers a wide variety of articles about social learning theory book, easily find your social learning theory book information here online.

economy, politics, society, psychology, biology, computer and so on, becoming a research hotspot. Evolutionary game theory is regarded as one of the most powerful tools to study cooperative behavior.According to the data of China Statistical Yearbook 2012, at the end of 2012, the number of college students in the country was 25,365,647. College students are the middle power of the future society, and also an important part of maintaining

I love learning, learning makes me happy.But maths makes me vomit blood.This article will be a rough summary of some basic number theory knowledge, and the blogger has done a number of mathematical knowledge of high-demand topics.But so far, bloggers have nothing to do, so there's basically nothing here.First, Euclidean algorithmSecond, expand Euclidean algorithm

The first two articles describe our research work on the understanding of user movement laws, including how to deal with missing data in user trajectories and how to recommend places of interest to users. In this section, I will present our research projects on user characterization .LifespecFirst of all, I would like to introduce our recently launched Lifespec project. The goal of this project is to use user data from social networks to explore all a

Deep Learning Book recommendation, deep learning bookAI Bible
Classic best-selling book in the field of deep learning! Has long ranked first in Amazon AI and machine learning books in the United States! All data scientists

data mining.3. Applied to social networks, turned into network science.4. Applied to natural language processing, turned into statistical natural language processing (there are many errors, all when entertainment).5. Should go to your field .... Suddenly....。。。。Part III: Machine learning Applications: Learn from the application, not much to say.(The book is here

Foundation in one of the best (hope not offend other departments of classmates), teaching hours is second only to the mathematics department, but after learning the effect is almost the bottom of the first. The reason for this is thought-provoking.My humble opinion is: Computer class students, the requirements of mathematics is different from the mathematical system, and the physical difference is greater. The so-called "higher mathematics", usually

://blog.sina.com.cn/s/blog_68f262210100mape.htmlHttp://jingyan.baidu.com/article/851fbc37d844553e1f15abe1.html2 Import Java.lang.Math;Be familiar with the arithmetic of math class;Extension: http://wxb-j2ee.iteye.com/blog/1010258http://blog.csdn.net/lixiang0522/article/details/7557851Http://www.cnblogs.com/ksuifeng/archive/2010/03/24/1693856.html3 Import Java.util.Comparator;Import java.util.Collections;familiar with comparator and collections class, combine ArrayList class, realize array sort;E

Https://github.com/josephmisiti/awesome-machine-learning/blob/master/books.mdMachine-learning/data Mining
An Introduction to statistical learning-book + R Code
Elements of statistical Learning-book
Probabilistic Programmin

field of statistics and extends to new areas such as data mining, machine learning and bioinformatics. machine Learning (Mitchell): Demonstrates the core algorithms and theories in machine learning, and illustrates the process of the algorithm's operation. Machine learning combines a number of research results, such a

From: http://blog.sina.com.cn/s/blog_50f98dfa0100a86r.html
Introduction to metacognitive theory and learning, edited by bloggers
The most important teaching is to teach students to learn, and the most important learning is to learn. In recent years, many large, medium, and primary schools in China have carried out teaching of

Original writing, reproduced please indicate the source of http://www.cnblogs.com/xbinworld/archive/2013/04/25/3041505.html
Today I will start learning pattern recognition and machine learning (PRML), Chapter 1.2, probability theory (I)
This section describes the essence of probability theory in the entire

Original writing. For reprint, please indicate that this article is from:Http://blog.csdn.net/xbinworld, Bin Column
Pattern Recognition and machine learning (PRML), Chapter 1.2, probability theory (I)
This section describes the essence of probability theory in the entire book, highlighting an uncertainty understand

In a twinkling of an eye, I started school for two months. In the middle, I had to spend a month or so on learning discrete mathematics because of some disgusting things, summarize the learning content, methods, and books.First, what exactly does discrete mathematics contain? Traditional lecture methods include mathematical logic, set theory, algebra system, and

In the recent learning Pattern recognition and machine learning often use the knowledge of probability theory, simply re-review the knowledge of probability theory. The most important point of learning probability theory is not th

, compactness , and metric spaces, which is the fundamentals that has to grasped before embarking on more advanced subjects such a s real analysis.Introductory functional analysis with applicationsErwin KreyszigIt's a very well written book on functional an analysis of that I-would like-to-recommend to every one who would like to study This is subject for the first time. Starting from simple notions such as metrics and norms, the

questions about Windows development, please read Petzold's book.
This book covers all aspects of Windows programming, including every element of Windows Programming (such as input, output and dialog box, graphics, multimedia, threads, documents and views, Internet, etc) the explanation is clear and concise. Most examples are representative examples. The Code style is good and practical. I think this

have any questions about Windows development, please read Petzold's work ."
Famous saying .
This book covers all aspects of Windows programming, including every element of Windows Programming (such as input, output and dialog box, graphics, multimedia, threads, documents and views, Internet, etc) the explanation is clear and concise. Most of the examples are representative examples,
Code Good style and practical value. I think this

content is more extensive.Probability statistics:Dimitri P.bertsekas, John n.tsitsiklis "Introduction to Probability"A relatively easy-to-understand probability theory textbookChristian P. Robert, George Casella "Monte Carlo statistical Methods"The application of Monte Carlo method in machine learning should be needless to say in the monograph of Monte Carlo method. Read a few similar textbooks, the feelin

Recommended for Android development books: From Getting started to mastering the series Learning Route book IntroductionTransferred from: http://blog.csdn.net/findsafety/article/details/52317506Many times we will continue to receive questions from beginners, "What are the classic introductory materials and learning routes for Android?" "," What are the recommenda

Let's continue the discussion of reading Vapnik ' s book Statistical Learning theory. In the very beginning of the book, Vapnik first described and the fundamental approaches in pattern recognition:the Parametri C Estimation approach and the non-parametric estimation approach. Before introducing the non-parametric appr

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