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qw123
- 计算机能自动连续地工作，是由程序控制而实现的，程序是用程序设计语言按任务的要求事先编写的。程序设计语言按发展过程分为：机器语言、汇编语言和高级语言。-computer automatically consecutive work is programmed to achieve the procedure is used programming language by the requirements of prior preparation. By programming language d
javaforBPandrbf
- 用java编写的bp网络和rbf网络的源程序 JNNT由java语言写成，具有跨平台的优越性能.java applet的演示版更简单到只需要任何机器上的浏览器就可以运行，无需安装任何大型附加软件。更方便爱好者通过internet远程访问资源。 -with java bp prepared by the network and the networks of the source rbf JNNT by java language, cross-platform advantages ca
websphinx-src
- 一个用java语言编写的网络爬虫程序，其中包含一个jar包，在装有jre的机器上可直接运行。-use a java language network Reptile procedures, which include a jar packs, jre installed in the machine can run.
mallet-0.4.tar
- mallet是自然语言处理、机器学习领域的一个开源项目。-mallet is a natural language processing, machine learning areas of a revenue item.
weka
- :<<数据挖掘--实用机器学习技术及java实现>>一书的配套源程序，结合数据挖掘和机器学习的知识,以java语言实现了具有代表性的各类数据挖掘方法.例如:classifier中的ZeroR.OneR.NaiveBayes.DecisionTable.IBK.C45,还有聚类,数据预处理等-: lt; Lt; Data Mining -- Practical Machine Learning Technology and java achieve gt; Gt; A ma
基于有限状态机的汉语数字语音端点检测
- 基于有限状态机的汉语数字语音端点检测.rar.rar格式为ｖｉｐ-based on the finite state machine language digital voice endpoint detection. Rar.rar format vip
mlclass-ex1_complete
- 机器学习算法实现使用octave语言，初级简单练习，斯坦福大学在线课程-Machine learning algorithm using octave language, primary simple exercise, Stanford university online courses
958346svmlight
- 支持向量机分类器 训练器 可以直接使用 C++语言实现 SVMLight-Support Vector Machine classifier training can direct the use of C++ language SVMLight
Machine-Learning-Java
- 机器学习算法利用JAVA语言实现，包括朴素贝叶斯算法，ID3算法等各种机器学习算法-Machine learning algorithms using JAVA language, including the Naive Bayes algorithm, ID3 algorithm and other machine learning algorithms
SGA
- 基本遗传算法的C语言源程序。（遗传算法的应用范围极其广泛，它可应用于函数优化、组合优化、生产调度问题、自动控制、机器人学、图像处理、人工生命、遗传编程以及机器学习等领域。）-Basic genetic algorithm C language source code. (Genetic algorithm extremely broad range of applications, it can be applied to function optimization, combinatorial
MSVMforproteins.tar
- 多分类支持向机C语言源代码.内含祥细使用说明及应用例子与数据.-Multiple classifiers to support the C language source code machine.祥细contains examples of use and application and data.
machine-learning-2
- 机器学习算法之C4.5与CART，经典的机器学习的外文资料，该资料描述详细，便于大家的学习。-The machine learning algorithm C4.5 and CART, the classical machine learning foreign language information, the information described in detail, easy to learn from everyone.
machine-learning-3
- 机器学习算法之EM与K-MEANS，经典的机器学习的外文资料，该资料描述详细，便于大家的学习。-The EM machine learning algorithms with K-MEANS, classical machine learning foreign language information, the information described in detail, easy to learn from everyone.
machine-learning-4
- 机器学习算法之KNN与PageRank，经典的机器学习的外文资料，该资料描述详细，便于大家的学习。-The KNN machine learning algorithm and PageRank, classical machine learning foreign language information, the information described in detail, easy to learn from everyone.
machine-learning-5
- 机器学习算法之SVM与朴素贝叶斯，经典的机器学习的外文资料，该资料描述详细，便于大家的学习。-Machine learning algorithms of SVM and Naive Bayes, classical machine learning foreign language information, the information described in detail, easy to learn from everyone.
Machine-Learning-in-Action
- 机器学习实战的英文版 实现语言为python 包含多种机器学习算法-The English version of machine learning practical implementation language for python contains a variety of machine learning algorithms
natural-language-processing
- 统计自然语言处理PPT-刘挺 中科院自动化研究所、模式识别国家重点实验室的 介绍的内容有统计机器翻译、词法分析与词性标注、语料库与词汇知识库-Statistical Natural Language Processing PPT-Ting Liu Institute of Automation, Chinese Academy of Sciences, State Key Laboratory of Pattern Recognition content presentation of
Python-Machine-Learning-Blueprints-master
- Python 是当前普遍使用的流行语言，并纳入了科学计算和机器学习的内容，本文件是一个Python机器学习工具包。(Python is a popular language currently used and incorporated into the contents of scientific computing and machine learning. This document is a Python machine learning toolkit.)
machine_learning_mastery_with_r_code
- r programming machine learning
Learning Deep Architectures for AI
- 一本关于深度架构学习算法，尤其是用来构造更深层模型的非监督学习的单层模型。(Theoretical results suggest that in order to learn the kind of com- plicated functions that can represent high-level abstractions (e.g., in vision, language, and other AI-level tasks), one may need deep archite