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其他书籍 by Randal L. Schwartz and Tom Phoenix ISBN 0-596-00132-0 Third Edition, published July 2001. (See
by Randal L. Schwartz and Tom Phoenix
ISBN 0-596-00132-0
Third Edition, published July 2001.
(See the catalog page for this book.)
Learning Perl, 3rd Edition.
Table of Contents
Copyright Page
Preface
Chapter 1: Introduction
Chapter 2: Scalar Data
Chapter 3: Lists and Arrays
Chapter 4: Subroutin ...
人工智能/神经网络 一个由Mike Gashler完成的机器学习方面的includes neural net, naive bayesian classifier, decision tree, KNN, a genet
一个由Mike Gashler完成的机器学习方面的includes neural net, naive bayesian classifier, decision tree, KNN, a genetic algorithm, and some manifold learning algorithms.
人工智能/神经网络 a Java toolkit for training, testing, and applying Bayesian Network Classifiers. Implemented classif
a Java toolkit for training, testing, and applying Bayesian Network Classifiers. Implemented classifiers have been shown to perform well in a variety of artificial intelligence, machine learning, and data mining applications.
软件设计/软件工程 Java Regex Primer Since version 1.4, Java has had support for Regular Expressions in the core API. J
Java Regex Primer Since version 1.4, Java has had support for Regular Expressions in the core API. Java Regex follows the same basic principles used in other languages, just withdi erent access methods, and some subtledi erences with the patterns. This primer is aimed towards developers already fami ...
其他 If you design applications, or if you build, test, or document solutions, you need this book. If you
If you design applications, or if you build, test, or document solutions, you need this book. If your applications are Web-based or Win32-based, you need this book. Finally, if you are currently learning or building Microsoft .NET Framework–based applications, you need this book. In short, if you a ...
其他 This data set contains WWW-pages collected from computer science departments of various universities
This data set contains WWW-pages collected from computer science departments of various universities in January 1997 by the World Wide Knowledge Base (Web->Kb) project of the CMU text learning group. The 8,282 pages were manually classified into the following categories:
student (1641)
faculty (11 ...
FlashMX/Flex源码 Introduction to neural networks, Back Propagation networks, Recurrent networks, Self Oganising netwo
Introduction to neural networks, Back Propagation networks, Recurrent networks, Self Oganising networks, Reinforcement learning. Robot Control, Vision systems. Hardware and software Implementaionts.