数据集(三)|人工智能领域100+数据集分享,赶紧收藏!

栏目:云星空知识作者:金蝶来源:金蝶云社区发布:2024-09-16浏览:3

数据集(三)|人工智能领域100+数据集分享,赶紧收藏!

学习数据分析需要持续进行实操,但很多读者找不到合适的数据集来练手,小编整理了人工智能领域100+数据集,总有一个是适合你练手的数据集!赶紧收藏点赞吧!




01、NLP语料库数据集


1.2016-2019新闻联播语料库(11.3MB)

https://www.heywhale.com/mw/dataset/5d2d344c688d36002c5da8e5


2.中文谣言语料库(32.6MB)

https://www.heywhale.com/mw/dataset/5d257f87688d36002c579342


3.中国对联数据集(28.2MB)

https://www.heywhale.com/mw/dataset/5c46e6f42d8ef5002b736d6d


4.1998人民日报标注语料库(PFR)(10.2MB)

https://www.heywhale.com/mw/dataset/5ce7983cd10470002b334de3


5.人民日报文章数据集(1979-2010)(811.9MB)

https://www.heywhale.com/mw/dataset/5c862b1ad635ff002ca2eb19


6.人民日报文章数据集(1949-1978)(559.4MB)

https://www.heywhale.com/mw/dataset/5c8626031e7104002b380a4b


7.中文新闻数据集(70.3MB)

https://www.heywhale.com/mw/dataset/5d8878638499bc002c1148f7


8.耶鲁文本转SQL语句挑战数据集(95.1MB)

https://www.heywhale.com/mw/dataset/5d48f322c143cf002bf36319


9.新加坡国立大学SMS语料库(23.4MB)

https://www.heywhale.com/mw/dataset/5d3ea76acf76a600361e9aa0


10.中文经典典籍语料

https://www.heywhale.com/mw/dataset/5d11e717708b90002c4d2983


11.非正式汉语数据集(214.5MB)

https://www.heywhale.com/mw/dataset/5d1c45459f53a9002ce35b61


12.维基百科中文语料库(518.7MB)

https://www.heywhale.com/mw/dataset/5d1ee7939f53a9002ce5910e


13.频率最高的9933个最常用汉字数据集(1.0MB)

https://www.heywhale.com/mw/dataset/5d8dd076037db3002d3a715c


14.聊天语料库数据集(210.7MB)

https://www.heywhale.com/mw/dataset/5dee1459953ca8002c9678a6


15.短文本分类数据集(13.1MB)

https://www.heywhale.com/mw/dataset/5dd645fca0cb22002c94e65d/file


16.成语阅读理解数据集(195.8MB)

https://www.heywhale.com/mw/dataset/5ddf91e8ca27f8002c4ad48d


17.论文自动评分数据集(78.8MB)

https://www.heywhale.com/mw/dataset/5de0c5ccca27f8002c4b178a


18.翻译语料(595.9MB)

https://www.heywhale.com/mw/dataset/5de5fcafca27f8002c4ca993


19.中文科学文献摘要数据集(92.9MB)

https://www.heywhale.com/mw/dataset/5de72db2ca27f8002c4ce7b4


20.维基百科英文语料库(89.0MB)

https://www.heywhale.com/mw/dataset/5ddba2c9f41512002cebfef6


21.Lord of the Rings指环王数据(223.9KB)

https://www.heywhale.com/mw/dataset/5da83b27c83fb400420c5707


22.中文机器阅读理解的跨度提取数据集(CMRC 2018)

https://www.heywhale.com/mw/dataset/5e7b180798d4a8002d2d3af6


23.36氪新闻数据集(42.5MB)

https://www.heywhale.com/mw/dataset/5eb68e91366f4d002d77d08d


24.1万条亚马逊乐器的评测/评论(13MB)

https://www.heywhale.com/mw/dataset/5e980ce4ebb37f002c5feccc


25.1万条互联网专栏资讯数据集(75.7MB)

https://www.heywhale.com/mw/dataset/5ebba2de0bff1b002ce6d6a7


26.2万条中文金融新闻数据集(66.6MB)

https://www.heywhale.com/mw/dataset/5eb69242366f4d002d77d2b7


27.中文图书分类数据集(49.8MB)

https://www.heywhale.com/mw/dataset/5ecf5a25162df90036ddec65


28.英文歌词数据集(69.1MB)

https://www.heywhale.com/mw/dataset/5aab8085afaabd5e93e4e027


29.特朗普政府发表的声明和简报(63.6MB)

https://www.heywhale.com/mw/dataset/5fae515f7d1e6d0030d68088



02、问答类数据集



1.金融行业问答数据集(245.5MB)


https://www.heywhale.com/mw/dataset/5e9588f8e7ec38002d0331b1


2.社区问答数据集(1.7GB)

https://www.heywhale.com/mw/dataset/5de601f3ca27f8002c4cac47


3.中文医学问答数据集(85MB)

https://www.heywhale.com/mw/dataset/5d313070cf76a60036e4b023


4.CNN 新闻文章中的 12 万个问答对数据集(17.3MB)

https://www.heywhale.com/mw/dataset/5eef1408caa99b002d6e37cc






03、情感分析类数据集


1.斯坦福情绪树库:带有情感注释的标准情绪数据集(6.1MB)

https://www.heywhale.com/mw/dataset/5daa748c1035d8002c35cdee


2.关于美国的航空公司的推特的情绪分析数据集(2.6MB)

https://www.heywhale.com/mw/dataset/5dab23781035d8002c3634c9


3.中文对话情绪语料(1.1MB)

https://www.heywhale.com/mw/dataset/5d00c390e727f8002c4599ad


4.多域情感数据集(51.2MB)

https://www.heywhale.com/mw/dataset/5de5ce0aca27f8002c4c9ee8


5.sentiment140 情感分析数据集(72.6KB)

https://www.heywhale.com/mw/dataset/5ca46f1a8408c1002b498cca



04、爬虫类数据集


1.6000条周杰伦微博超话数据!(1.1MB)

https://www.heywhale.com/mw/dataset/5d3551bdcf76a60036f605aa


2.《中餐厅3》19W弹幕数据(12.8MB)

https://www.heywhale.com/mw/dataset/5d7b69798499bc002c0d3ec5


3.bilibili流行动漫影评数据(2.3MB)

https://www.heywhale.com/mw/dataset/5d3a76dfcf76a600360e19c9


4.淘宝某店铺电风扇评论(273.9KB)

https://www.heywhale.com/mw/dataset/5d442caec143cf002bdb687c


5.7K条马蜂窝国内热门景点游记(140+MB)

https://www.heywhale.com/mw/dataset/5e7c55db98d4a8002d2db5a2


6.IMDB电影评论数据(32.0MB)

https://www.heywhale.com/mw/dataset/5d143d41708b90002c5f7021


7.未名BBS热门话题(3.6MB)

https://www.heywhale.com/mw/dataset/5dad84b375df5c002b20d79f


8.咪蒙所有公众号文章(3.9MB)

https://www.heywhale.com/mw/dataset/5c8723441e7104002b3831d3


9.6000条周杰伦微博超话数据(1.1MB)

https://www.heywhale.com/mw/dataset/5d3551bdcf76a60036f605aa


10.麦当劳就餐负面评论数据集(891.1KB)

https://www.heywhale.com/mw/dataset/5dab2c0b1035d8002c36372b



05、实体识别类数据集


1.用于命名实体识别的带注释语料库(26.4MB)

https://www.heywhale.com/mw/dataset/5de9be34953ca8002c95c35f


2.使用LatticeLSTM的中文NER数据(191.5KB)

https://www.heywhale.com/mw/dataset/5d564ea0c143cf002b235181


3.医疗命名实体识别数据集(5.1MB)

https://www.heywhale.com/mw/dataset/5dedef59953ca8002c96667a


4.中文实体关系抽取数据集(8.1MB)

https://www.heywhale.com/mw/dataset/5dde487dca27f8002c4a8352


5.金融信息负面及主体判定比赛数据集(17MB)

https://www.heywhale.com/mw/dataset/5e09a9eb2823a10036b126c0




06、CV类数据集



1.Pronto共享单车数据集(70.8MB)

https://www.heywhale.com/mw/dataset/58a515c48460306efcce2e96



1.Fashion-MNIST图像数据集(200.4MB)

https://www.heywhale.com/mw/dataset/5a0cfcf860680b295c28a753


2.CIFAR100数据集(161.3MB)

https://www.heywhale.com/mw/dataset/5e96da12e7ec38002d03bf51


3.车辆数据集(车辆识别与分类)(62.5MB)

https://www.heywhale.com/mw/dataset/5bc316173631bc00109d2abf


4.垃圾分类数据集

https://www.heywhale.com/mw/dataset/5d133d11708b90002c570588


5.另一个垃圾分类数据集(40.9MB)

https://www.heywhale.com/mw/dataset/5d1578e4708b90002c6a3238


6.CIFAR10数据集(148MB)

https://www.heywhale.com/mw/dataset/5ab3403bfdf6b86c23f259e3


7.GTSRB-德国交通标志识别图像数据(253.3MB)

https://www.heywhale.com/mw/dataset/5d8db5ca037db3002d3a5ba0


8.手势识别数据库(1.1GB)

https://www.heywhale.com/mw/dataset/5d8da999037db3002d3a523


9.情绪的面部表情(170MB+)

https://www.heywhale.com/mw/dataset/5d773bd68499bc002c0c4a6f


10.枪支目标检测(2.4MB)

https://www.heywhale.com/mw/dataset/5d576984c143cf002b238528


11.人脸图像数据(294.1MB)

https://www.heywhale.com/mw/dataset/5da6d4cac83fb4004206edf0


12.RMFD口罩遮挡人脸数据集(610.3MB)

https://www.heywhale.com/mw/dataset/5e81a24b246a590036b884d5


13.中国交警手势数据集(1.8GB)

https://www.heywhale.com/mw/dataset/5de75df5ca27f8002c4cf1bb


14.场景分类数据集(105.9MB)

https://www.heywhale.com/mw/dataset/5ddb4adef41512002cebc776


15.87种宝石图片数据(50.9MB)

https://www.heywhale.com/mw/dataset/5ddccb4aca27f8002c4a26db


16.验证码数据集(13.5MB)

https://www.heywhale.com/mw/dataset/5e143ef32823a10036b34846/file


17.硬币图像数据集(326.7MB)

https://www.heywhale.com/mw/dataset/5e7c7b3e98d4a8002d2dd15c


18.LabelMe图像语义分割数据集(102.6MB)

https://www.heywhale.com/mw/dataset/5e7b770698d4a8002d2d7925


19.车牌识别数据集(62.8MB)

https://www.heywhale.com/mw/dataset/5e96cf8fe7ec38002d03b8ed


20.Biwi头姿势数据库(449.7MB)

https://www.heywhale.com/mw/dataset/5ea16e79105d91002d4f4a25


动物

21.Butterfly-200细粒度图像分类数据集(828MB)

https://www.heywhale.com/mw/dataset/5e85d97095b029002ca7e904


22.宠物图像数据集(783.5MB)

https://www.heywhale.com/mw/dataset/5d76060b8499bc002c0bdd66


23.狗狗种类图像数据集(919.5MB)

https://www.heywhale.com/mw/dataset/5def46de2823a10036aab2f5


24.黑猩猩图片数据集(604.4MB)

https://www.heywhale.com/mw/dataset/5e7b62da98d4a8002d2d6deb


植物:

25.水稻叶子疾病图片集(36.7MB)

https://www.heywhale.com/mw/dataset/5d522069c143cf002b21edbb


26.植物幼苗图片数据集

https://www.heywhale.com/mw/dataset/5d4cd153c143cf002b0a8d4f


27.花卉识别数据集(224.9MB)

https://www.heywhale.com/mw/dataset/5cc127b98c90d7002c8375d7


28.花卉图像分类

https://www.heywhale.com/mw/dataset/5d3320afcf76a60036ec5fd1


29.可食用野外植物数据集

https://www.heywhale.com/mw/dataset/5d4a5e88c143cf002bfbf5d0


30.叶片计数图像数据集(882.3MB)

https://www.heywhale.com/mw/dataset/5e841900246a590036b954bd


气象:

31.飓风损害的卫星图像数据集(63MB)

https://www.heywhale.com/mw/dataset/5da6e8a6c83fb40042073e4f


32.从卫星图像理解云层数据集(42MB)

https://www.heywhale.com/mw/dataset/5dafcd9275df5c002b2189c6


字符识别:

33.TibetanMNIST藏文手写数字数据集(53.2MB)

https://www.heywhale.com/mw/dataset/5bfe734a954d6e0010683839


34.MNIST手写识别数据集(9.5MB)

https://www.heywhale.com/mw/dataset/58a7c84c803d1a0d2e26441a


35.Chars74K字符识别数据集(188.3MB)

https://www.heywhale.com/mw/dataset/5d89c020e3ffb2002c44fb0a


36.信用卡卡面图像及标注数据(42.9MB)

https://www.heywhale.com/mw/dataset/5954cf1372ead054a5e25870


37.手写数学表达式识别(29MB)

https://www.heywhale.com/mw/dataset/5daff66f75df5c002b219fb0


38.图片与单词匹配数据集(31.1MB)

https://www.heywhale.com/mw/dataset/5dab27631035d8002c3635eb


39.密集不规则文本行数据集(353MB)

https://www.heywhale.com/mw/dataset/5da95febc83fb400420f3631


40.视觉文字识别数据集

https://www.heywhale.com/mw/dataset/5df058762823a10036aae665


41.HASY手写符号图片数据集(127.2MB)

https://www.heywhale.com/mw/dataset/5dee0b25953ca8002c9671ea


42.麻将图片数据集(7.5MB)

https://www.heywhale.com/mw/dataset/5de76474ca27f8002c4cf44c



医疗:

43.犬球虫病寄生虫图片集(18.1MB)

https://www.heywhale.com/mw/dataset/5d4cd9c7c143cf002b0abead


44.头部CT图像数据(24.4MB)

https://www.heywhale.com/mw/dataset/5d7213eb8499bc002c0af1e8


45.肺部CT图像数据(529.0MB)

https://www.heywhale.com/mw/dataset/5d71de448499bc002c0ae1fc


46.心血管疾病预测(2.7MB)

https://www.heywhale.com/mw/dataset/5db00b9175df5c002b21af83/file


47.深圳医院胸片检查掩膜图片数据集(19.8MB)

https://www.heywhale.com/mw/dataset/5daff18575df5c002b219c89


48.肺部CT图像数据(529MB)

https://www.heywhale.com/mw/dataset/5d71de448499bc002c0ae1fc


49.结核病图像数据集(456.8MB)

https://www.heywhale.com/mw/dataset/5efc4de063975d002c9792de



行人识别:

50.行人检测数据集ETHZ(146MB)

https://www.heywhale.com/mw/dataset/5db2680f75df5c002b23b755


51.行人重识别数据集Market-1501(145.7MB)

https://www.heywhale.com/mw/dataset/5db148b375df5c002b2295dd


52.行人重识别数据集RAiD(140.1MB)

https://www.heywhale.com/mw/dataset/5db11bf775df5c002b226914


53.行人重识别数据集prid_2011(1015.3MB)

https://www.heywhale.com/mw/dataset/5db10d1a75df5c002b2259dd


54.汽车后视摄像头视角行人数据集(799.7MB)

https://www.heywhale.com/mw/dataset/5dafc75175df5c002b2186a0




07、语音类数据集


1.Mozilla语音数据集-中文(358.2MB)

https://www.heywhale.com/mw/dataset/5d6f91678499bc002c0a722b


2.2000个英语读数字的录音(8.9MB)

https://www.heywhale.com/mw/dataset/5ddde933ca27f8002c4a6013






延伸阅读:

【1】数据分析师如何构建数据指标体系?理解以下四个模型就够了!

https://wenku.my7c.com/article/296943831369590016


【2】数据分析师如何正确的提建议?

https://wenku.my7c.com/article/296937594120846336


【3】数据集(二)|10个领域70+数据集分享,赶紧收藏!

https://wenku.my7c.com/article/297369594749271040


【4】数据集|7个领域70+数据集分享,赶紧收藏!

https://wenku.my7c.com/article/297370766855467520


来源:微信公众号【数据万花筒】


感谢分享

数据集(三)|人工智能领域100+数据集分享,赶紧收藏!

学习数据分析需要持续进行实操,但很多读者找不到合适的数据集来练手,小编整理了人工智能领域100+数据集,总有一个是适合你练手的数据集!...
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