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Title: GitHub - stanWhy/AiLearning: AiLearning: 机器学习 - MachineLearning - ML、深度学习 - DeepLearning - DL、自然语言处理 NLP

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Description: AiLearning: 机器学习 - MachineLearning - ML、深度学习 - DeepLearning - DL、自然语言处理 NLP - stanWhy/AiLearning

Open Graph Description: AiLearning: 机器学习 - MachineLearning - ML、深度学习 - DeepLearning - DL、自然语言处理 NLP - stanWhy/AiLearning

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https://patch-diff.githubusercontent.com/stanWhy/AiLearning#1机器学习---基础
ApacheCN(apache中文网)http://cwiki.apachecn.org/
【机器学习实战-中文版-带目录版.pdf】https://github.com/apachecn/AiLearning/tree/master/books
飞龙小哥哥https://github.com/wizardforcel
《机器学习实战-ApacheCN.pdf》https://github.com/apachecn/AiLearning/blob/master/books/%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0%E5%AE%9E%E6%88%98-ApacheCN.pdf
群小哥哥：红色石头https://github.com/RedstoneWill
台湾大学林轩田机器学习笔记https://github.com/apachecn/ntu-hsuantienlin-ml
机器学习笔记https://feisky.xyz/machine-learning
https://feisky.xyz/machine-learninghttps://feisky.xyz/machine-learning
第 1 章: 机器学习基础https://patch-diff.githubusercontent.com/stanWhy/AiLearning/blob/dev/blog/ml/1.机器学习基础.md
@毛红动https://github.com/ElmaDavies
第 2 章: KNN 近邻算法https://patch-diff.githubusercontent.com/stanWhy/AiLearning/blob/dev/blog/ml/2.k-近邻算法.md
@尤永江https://github.com/youyj521
第 3 章: 决策树https://patch-diff.githubusercontent.com/stanWhy/AiLearning/blob/dev/blog/ml/3.决策树.md
@景涛https://github.com/jingwangfei
第 4 章: 朴素贝叶斯https://patch-diff.githubusercontent.com/stanWhy/AiLearning/blob/dev/blog/ml/4.朴素贝叶斯.md
@wnma3mzhttps://github.com/wnma3mz
@分析https://github.com/kailian
第 5 章: Logistic回归https://patch-diff.githubusercontent.com/stanWhy/AiLearning/blob/dev/blog/ml/5.Logistic回归.md
@微光同尘https://github.com/DataMonk2017
第 6 章: SVM 支持向量机https://patch-diff.githubusercontent.com/stanWhy/AiLearning/blob/dev/blog/ml/6.支持向量机.md
@王德红https://github.com/VPrincekin
第 7 章: 集成方法（随机森林和 AdaBoost）https://patch-diff.githubusercontent.com/stanWhy/AiLearning/blob/dev/blog/ml/7.集成方法-随机森林和AdaBoost.md
@片刻https://github.com/jiangzhonglian
第 8 章: 回归https://patch-diff.githubusercontent.com/stanWhy/AiLearning/blob/dev/blog/ml/8.回归.md
@微光同尘https://github.com/DataMonk2017
第 9 章: 树回归https://patch-diff.githubusercontent.com/stanWhy/AiLearning/blob/dev/blog/ml/9.树回归.md
@微光同尘https://github.com/DataMonk2017
第 10 章: K-Means 聚类https://patch-diff.githubusercontent.com/stanWhy/AiLearning/blob/dev/blog/ml/10.k-means聚类.md
@徐昭清https://github.com/xuzhaoqing
第 11 章: 利用 Apriori 算法进行关联分析https://patch-diff.githubusercontent.com/stanWhy/AiLearning/blob/dev/blog/ml/11.使用Apriori算法进行关联分析.md
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第 12 章: FP-growth 高效发现频繁项集https://patch-diff.githubusercontent.com/stanWhy/AiLearning/blob/dev/blog/ml/12.使用FP-growth算法来高效发现频繁项集.md
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第 13 章: 利用 PCA 来简化数据https://patch-diff.githubusercontent.com/stanWhy/AiLearning/blob/dev/blog/ml/13.利用PCA来简化数据.md
@廖立娟https://github.com/lljuan330
第 14 章: 利用 SVD 来简化数据https://patch-diff.githubusercontent.com/stanWhy/AiLearning/blob/dev/blog/ml/14.利用SVD简化数据.md
@张俊皓https://github.com/marsjhao
第 15 章: 大数据与 MapReducehttps://patch-diff.githubusercontent.com/stanWhy/AiLearning/blob/dev/blog/ml/15.大数据与MapReduce.md
@wnma3mzhttps://github.com/wnma3mz
第 16 章: 推荐系统（已迁移）https://patch-diff.githubusercontent.com/stanWhy/AiLearning/blob/dev/blog/ml/16.推荐系统.md
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知乎问答-爆炸啦-机器学习该怎么入门？https://www.zhihu.com/question/20691338/answer/248678328
MachineLearning(机器学习) 学习路线图http://www.apachecn.org/map/145.html
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可汗学院(统计学)http://open.163.com/special/Khan/khstatistics.html
可汗学院(线性代数)http://open.163.com/special/Khan/linearalgebra.html
http://www.acfun.cn/u/12540256.aspx#page=1
https://space.bilibili.com/97678687/#!/channel/index
http://i.youku.com/apachecn
http://study.163.com/course/courseMain.htm?courseId=1004582003
吴恩达机器学习http://study.163.com/course/courseMain.htm?courseId=1004570029
神经网络和深度学习http://mooc.study.163.com/course/2001281002?tid=2001392029
https://patch-diff.githubusercontent.com/stanWhy/AiLearning#2深度学习---基础
https://www.cnblogs.com/charlotte77/p/5629865.htmlhttps://www.cnblogs.com/charlotte77/p/5629865.html
http://www.cnblogs.com/charlotte77/p/7759802.htmlhttp://www.cnblogs.com/charlotte77/p/7759802.html
https://blog.csdn.net/qq_39422642/article/details/78676567https://blog.csdn.net/qq_39422642/article/details/78676567
https://blog.csdn.net/roslei/article/details/61912618https://blog.csdn.net/roslei/article/details/61912618
https://patch-diff.githubusercontent.com/stanWhy/AiLearning#3自然语言处理
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https://github.com/apachecn/AiLearning/tree/dev/blog/nlphttps://github.com/apachecn/AiLearning/tree/dev/blog/nlp
https://usyiyi.github.io/nlp-py-2e-zhhttps://usyiyi.github.io/nlp-py-2e-zh
liuhuanyong大佬https://github.com/liuhuanyong
https://liuhuanyong.github.iohttps://liuhuanyong.github.io
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https://patch-diff.githubusercontent.com/stanWhy/AiLearning#应用领域
https://patch-diff.githubusercontent.com/stanWhy/AiLearning#中文分词
https://patch-diff.githubusercontent.com/stanWhy/AiLearning#1文本分类text-classification
路透社Newswire主题分类http://kdd.ics.uci.edu/databases/reuters21578/reuters21578.html
另见RCV1，RCV2和TRC2http://trec.nist.gov/data/reuters/reuters.html
IMDB电影评论情感分类（斯坦福）http://ai.stanford.edu/~amaas/data/sentiment
新闻组电影评论情感分类（康奈尔）http://www.cs.cornell.edu/people/pabo/movie-review-data/
单标签文本分类的数据集http://ana.cachopo.org/datasets-for-single-label-text-categorization
https://www.kaggle.com/c/word2vec-nlp-tutorialhttps://www.kaggle.com/c/word2vec-nlp-tutorial
https://patch-diff.githubusercontent.com/stanWhy/AiLearning#2语言模型language-modeling
古腾堡项目https://www.gutenberg.org/
布朗大学现代美国英语标准语料库https://en.wikipedia.org/wiki/Brown_Corpus
谷歌10亿字语料库https://github.com/ciprian-chelba/1-billion-word-language-modeling-benchmark
https://github.com/zhanzecheng/Chinese_segment_augmenthttps://github.com/zhanzecheng/Chinese_segment_augment
https://www.kaggle.com/c/quora-question-pairshttps://www.kaggle.com/c/quora-question-pairs
https://patch-diff.githubusercontent.com/stanWhy/AiLearning#3图像字幕image-captioning
上下文中的公共对象（COCO）http://mscoco.org/dataset/#overview
Flickr 8Khttp://nlp.cs.illinois.edu/HockenmaierGroup/8k-pictures.html
Flickr 30Khttp://shannon.cs.illinois.edu/DenotationGraph/
探索图像字幕数据集，2016年http://sidgan.me/technical/2016/01/09/Exploring-Datasets
https://patch-diff.githubusercontent.com/stanWhy/AiLearning#4机器翻译machine-translation
加拿大第36届议会的协调国会议员https://www.isi.edu/natural-language/download/hansard/
欧洲议会诉讼平行语料库1996-2011http://www.statmt.org/europarl/
统计机器翻译http://www.statmt.org/
http://pytorch.apachecn.org/cn/tutorials/intermediate/seq2seq_translation_tutorial.htmlhttp://pytorch.apachecn.org/cn/tutorials/intermediate/seq2seq_translation_tutorial.html
https://patch-diff.githubusercontent.com/stanWhy/AiLearning#5问答系统question-answering
斯坦福问题回答数据集（SQuAD）https://rajpurkar.github.io/SQuAD-explorer/
Deepmind问题回答语料库https://github.com/deepmind/rc-data
亚马逊问答数据http://jmcauley.ucsd.edu/data/amazon/qa/
数据集：我如何获得问答网站的语料库，如Quora或Yahoo Answers或Stack Overflow来分析答案质量？https://www.quora.com/Datasets-How-can-I-get-corpus-of-a-question-answering-website-like-Quora-or-Yahoo-Answers-or-Stack-Overflow-for-analyzing-answer-quality
https://patch-diff.githubusercontent.com/stanWhy/AiLearning#6语音识别speech-recognition
TIMIT声学 - 语音连续语音语料库https://catalog.ldc.upenn.edu/LDC93S1
VoxForgehttp://voxforge.org/
LibriSpeech ASR语料库http://www.openslr.org/12/
https://patch-diff.githubusercontent.com/stanWhy/AiLearning#7自动文摘document-summarization
法律案例报告数据集https://archive.ics.uci.edu/ml/datasets/Legal+Case+Reports
TIPSTER文本摘要评估会议语料库http://www-nlpir.nist.gov/related_projects/tipster_summac/cmp_lg.html
英语新闻文本的AQUAINT语料库https://catalog.ldc.upenn.edu/LDC2002T31
文档理解会议（DUC）任务http://www-nlpir.nist.gov/projects/duc/data.html
在哪里可以找到用于文本摘要的良好数据集？https://www.quora.com/Where-can-I-find-good-data-sets-for-text-summarization
http://pytorch.apachecn.org/cn/tutorials/beginner/nlp/advanced_tutorial.htmlhttp://pytorch.apachecn.org/cn/tutorials/beginner/nlp/advanced_tutorial.html
https://www.jianshu.com/p/55755fc649b1https://www.jianshu.com/p/55755fc649b1
https://www.zhihu.com/question/44832436/answer/266068967https://www.zhihu.com/question/44832436/answer/266068967
https://blog.csdn.net/BaiHuaXiu123/article/details/77847232https://blog.csdn.net/BaiHuaXiu123/article/details/77847232
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维基百科研究中使用的文本数据集https://en.wikipedia.org/wiki/List_of_datasets_for_machine_learning_research#Text_data
数据集：计算语言学家和自然语言处理研究人员使用的主要文本语料库是什么？https://www.quora.com/Datasets-What-are-the-major-text-corpora-used-by-computational-linguists-and-natural-language-processing-researchers-and-what-are-the-characteristics-biases-of-each-corpus
斯坦福统计自然语言处理语料库https://nlp.stanford.edu/links/statnlp.html#Corpora
按字母顺序排列的NLP数据集列表https://github.com/niderhoff/nlp-datasets
该机构NLTKhttp://www.nltk.org/nltk_data/
在DL4J上打开深度学习数据https://deeplearning4j.org/opendata
NLP数据集https://github.com/caesar0301/awesome-public-datasets#natural-language
https://bosonnlp.com/dev/resourcehttps://bosonnlp.com/dev/resource
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