机器学习高端课程 机器读心术之文本挖掘与自然语言处理 炼数成金文本挖掘
课程称号: 机械进修高端课程 机械读心术之文本挖掘与自然说话处置 炼数成金文本挖掘
课程简介:
----------------------课程目录------------------------------
│├
││├NLP01.pdf
││├NLP0视频部分
││├统计自然说话处置根本.pdf
││├形式说话与自动机理论.pdf
││├自然说话处置综论.pdf
││└宗成庆统计自然说话处置 .pdf
│├
││├Error-tolerant Finite State Recognition.pdf
││├NLP02.pdf
││├NLP02视频部分
││└Tagging with Finite-State Transducers.pdf
│├
││├icslp2002-srilm.pdf
││├NLP03.pdf
││└NLP03视频部分
│├
││├crf-tutorial.pdf
││├nips01-discriminativegenerative.pdf
││├NLP04.pdf
││├NLP04视频部分
││├几率论与数理统计 第四版.pdf
││└几率图模子道理与技术.pdf
│├
││├EM算法具编制子及推导.pdf
││├hhmm.pdf
││├htk.rar
││├HTK.zip
││├NLP05.pdf
││├NLP05视频部分
││└The-EM-algorithm.pdf
│├
││├Conditional Random Fields An Introduction.pdf
││├crf.pdf
││├maxent.pdf
││├maxent_adwait97.pdf
││├Maximum Entropy Markov Models for Information Extraction and Segmentation.pdf
││├NLP06.pdf
││├NLP06视频部分
││├条件随机场综述.pdf
││└统计进修方式.pdf
│├
││├ActivePerl-5.22.1.2201-MSWin32-x86-64int-299574.msi
││├conlleval.pl
││├CRF++-0.58.zip
││├CRF++工具包利用先容.ppt
││├CRF++利用指南.docx
││├NLP07.pdf
││├NLP07视频部分
││└基于条件随机场的中文人名性别识别研讨.doc
│├
││├A Character-Based Joint Model for Chinese Word Segmentation.pdf
││├A Fast Decoder for Joint Word Segmentation and POS-Tagging Using a Single Discriminative Model.pdf
││├Chinese Segmentation with aWord-Based Perceptron Algorithm.pdf
││├Discriminative Training Methods for Hidden Markov Models Theory and Experiments with Perceptron Algorithms.pdf
││├Integrating Generative and Discriminative Character-Based Models for Chinese Word Segmentation.pdf
││├NLP08.pdf
││├NLP08视频部分
││├Syntactic Processing Using the GeneralizedPerceptron and Beam Search.pdf
││├Which is More Suitable for Chinese Word Segmentation the Generative Model or the Discriminative One.pdf
││├对自动分词的深思.pdf
││├基于N-最长途径方式的中文词语粗分模子.pdf
││├由字构词——中文分词新方式.pdf
││├中文分词十年回首.pdf
││└中文文本自动分词和标注_刘开瑛.pdf
│├
││├NLP09.pdf
││├NLP09视频部分
││└汉语问答系统关键技术研讨_吴友政.pdf
│├
││├语料库.mp4
││├语料库扶植.pdf
││└
│├
││├LDA及Gibbs-Sampling-yangliuy.pdf
││├LDA数学八卦.pdf
││├NLP10.pdf
││├NLP10视频部分
││├Parameter estimation for text analysis.pdf
││├PLSA及EM算法-yangliuy.pdf
││├Unsupervised Learning by Probabilistic Latent Semantic Analysis.pdf
││└一种自顺应词性标注方式.pdf
│├
││├A Sentimental Education Sentiment Analysis Using Subjectivity Summarization Based on Minimum Cuts.pdf
││├Joint Sentiment Topic Model for Sentiment Analysis.pdf
││├NLP11.pdf
││├NLP11视频部分
││├pcfgs.pdf
││├Thumbs up Sentiment Classification using Machine Learning Techniques.pdf
││├Using_appraisal_groups_for_sentiment_analysis.pdf
││└第11课作业素材.zip
│├
││├A Hybrid Approach to Chinese Base Noun Phrase Chunking.pdf
││├Catching the Drift Probabilistic Content Models.pdf
││├Centroid-based summarization of multiple documents.pdf
││├Coreference Resolution Current Trends and Future Directions.pdf
││├Fast Methods for Kernel-based Text Analysis.pdf
││├First-Order Probabilistic Models for Coreference Resolution.pdf
││├LATENT DIRICHLET LEARNING FOR DOCUMENT SUMMARIZATION.pdf
││├Layer-Based Dependency Parsing.pdf
││├NLP12.pdf
││├NLP12视频部分
││├Non-projective Dependency Parsing using Spanning Tree Algorithms.pdf
││├Online Large-Margin Training of Dependency Parsers.pdf
││├Sentence Fusion for Multidocument News Summarization.pdf
││├Shallow Parsing with Conditional Random Fields.pdf
││├Use ofSupport Vector Learning for Chunk Identification.pdf
││├基于潜伏语义分析的单文本自动摘要方式研讨.pdf
││├基于潜伏语义索引的文本摘要方式.PDF
││├文档摘要作业素材.zip
││└指代消解综述.pdf
│├
││├A STATISTICAL APPROACH TO MACHINE TRANSLATION.pdf
││├A Statistical MT Tutorial Workbook.pdf
││├A Survey on Question and Answering Systems.pdf
││├Building Watson.pdf
││├Discriminative Training and Maximum Entropy Models for Statistical Machine Translation.pdf
││├Erratum to A Statistical Approach to Machine Translation.pdf
││├HMM-Based Word Alignment in Statistical Translation.pdf
││├NLP13.pdf
││├NLP13a.mp4
││├NLP13b.mp4
││├NLP13c.mp4
││├NLP13d.mp4
││├NLP13e.mkv
││├NLP13f.mp4
││├NLP13g.mp4
││├NLP13h.mp4
││├Statistical Machine Translation -Koehn.pdf
││├The Mathematics of Statistical Machine Translation Parameter Estimation.pdf
││├谷歌翻译.pdf
││├基于FAQ的OTC问答系统的设想与实现.pdf
││├刘群-机械翻译道理与方式课本(03)基于词的统计机械翻译方式.pdf
└└└微信聊天机械设置流程.pdf
下载地址：**** Hidden Message *****
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