{"id":54096,"date":"2019-12-18T00:00:00","date_gmt":"2019-12-17T21:00:00","guid":{"rendered":"https:\/\/prohoster.info\/blog\/blog_prohoster\/52-dataseta-dlya-trenirovochnyh-proektov"},"modified":"2020-02-18T14:02:04","modified_gmt":"2020-02-18T11:02:04","slug":"52-dataseta-dlya-trenirovochnyh-proektov","status":"publish","type":"post","link":"https:\/\/prohoster.info\/pt\/blog\/news\/52-dataseta-dlya-trenirovochnyh-proektov","title":{"rendered":"52 conjuntos de dados para projetos de treinamento","gt_translate_keys":[{"key":"rendered","format":"text"}]},"content":{"rendered":"<ol>\n<li><noindex><a rel=\"nofollow\" href=\"https:\/\/www.kaggle.com\/shwetabh123\/mall-customers\">Conjunto de Dados de Clientes de Mall<\/a><\/noindex> \u2014 dados dos visitantes da loja: id, sexo, idade, renda, classifica\u00e7\u00e3o de gastos. (<i>Caso de uso: <noindex><a rel=\"nofollow\" href=\"https:\/\/data-flair.training\/blogs\/r-data-science-project-customer-segmentation\/\">Projeto de Segmenta\u00e7\u00e3o de Clientes com Aprendizado de M\u00e1quina<\/a><\/noindex><\/i>)<\/li>\n<li><noindex><a rel=\"nofollow\" href=\"https:\/\/archive.ics.uci.edu\/ml\/datasets\/Iris\">Conjunto de Dados Iris<\/a><\/noindex> \u2014 conjunto de dados para iniciantes, contendo as dimens\u00f5es das s\u00e9palas e p\u00e9talas de v\u00e1rias flores.<\/li>\n<li><noindex><a rel=\"nofollow\" href=\"http:\/\/yann.lecun.com\/exdb\/mnist\/\">Conjunto de Dados MNIST<\/a><\/noindex> \u2014 conjunto de dados de d\u00edgitos manuscritos. 60.000 imagens de treinamento e 10.000 imagens de teste.<\/li>\n<li><noindex><a rel=\"nofollow\" href=\"https:\/\/www.cs.toronto.edu\/~delve\/data\/boston\/bostonDetail.html\">O Conjunto de Dados de Habita\u00e7\u00e3o de Boston<\/a><\/noindex> \u2014 um conjunto de dados popular para reconhecimento de padr\u00f5es. Cont\u00e9m informa\u00e7\u00f5es sobre casas em Boston: n\u00famero de apartamentos, custo de aluguel, \u00edndice de criminalidade.<\/li>\n<li><noindex><a rel=\"nofollow\" href=\"https:\/\/www.kaggle.com\/c\/fake-news\/data\">Conjunto de Dados de Detec\u00e7\u00e3o de Fake News<\/a><\/noindex> \u2014 cont\u00e9m 7.796 registros com marca\u00e7\u00e3o de not\u00edcias: verdade ou mentira. (<i>Caso de uso com c\u00f3digo-fonte em Python: <noindex><a rel=\"nofollow\" href=\"https:\/\/data-flair.training\/blogs\/advanced-python-project-detecting-fake-news\/\">Projeto de Detec\u00e7\u00e3o de Fake News em Python <\/a><\/noindex><\/i>)<\/li>\n<li><noindex><a rel=\"nofollow\" href=\"https:\/\/archive.ics.uci.edu\/ml\/datasets\/wine+quality\">Conjunto de Dados sobre Qualidade do Vinho<\/a><\/noindex> \u2014 cont\u00e9m informa\u00e7\u00f5es sobre vinhos: 4.898 registros com 14 par\u00e2metros.<\/li>\n<li><noindex><a rel=\"nofollow\" href=\"http:\/\/wiki.stat.ucla.edu\/socr\/index.php\/SOCR_Data_Dinov_020108_HeightsWeights\">Dados SOCR \u2013 Conjunto de Dados de Alturas e Pesos<\/a><\/noindex> \u2014 uma boa op\u00e7\u00e3o para come\u00e7ar. Cont\u00e9m 25.000 registros sobre altura e peso de pessoas de 18 anos.<br \/>\n<blockquote><p><noindex><a rel=\"nofollow\" href=\"https:\/\/www.edsd.ru\/\" title=\"EDISON Software - desenvolvimento web\"><img decoding=\"async\" alt=\"52 conjuntos de dados para projetos de treinamento\" src=\"\/wp-content\/uploads\/2019\/12\/63d7c86bf20e229a14da7e4dd758d5df.png\" style=\"display:block;margin: 0 auto;\" \/><\/a><\/noindex><br clear=\"right\"><br \/>\nEste artigo foi traduzido com o apoio da empresa EDISON Software, que <noindex><a rel=\"nofollow\" href=\"https:\/\/www.edsd.ru\/ru\/o_kompanii\/novosti\/desyat-plyusov-edison\">realiza pedidos da China do Sul \"com excel\u00eancia\"<\/a><\/noindex>, al\u00e9m de <noindex><a rel=\"nofollow\" href=\"https:\/\/www.edsd.ru\/ru\/proekty\/sozdaniye_saytov\">desenvolve aplicativos e sites web<\/a><\/noindex>.<\/p><\/blockquote>\n<\/li>\n<li><noindex><a rel=\"nofollow\" href=\"https:\/\/archive.ics.uci.edu\/ml\/datasets\/parkinsons\">Conjunto de Dados de Parkinson<\/a><\/noindex> \u2014 195 registros de pacientes com a doen\u00e7a de Parkinson, com 25 par\u00e2metros de exames. Pode ser usado para avalia\u00e7\u00e3o preliminar da diferen\u00e7a entre pessoas doentes e saud\u00e1veis. (<i>Caso de uso com c\u00f3digo-fonte em Python: <noindex><a rel=\"nofollow\" href=\"https:\/\/data-flair.training\/blogs\/python-machine-learning-project-detecting-parkinson-disease\/\">Projeto de Aprendizado de M\u00e1quina para Detectar a Doen\u00e7a de Parkinson<\/a><\/noindex><\/i>)<\/li>\n<li><noindex><a rel=\"nofollow\" href=\"https:\/\/web.stanford.edu\/class\/archive\/cs\/cs109\/cs109.1166\/problem12.html\">Conjunto de Dados do Titanic<\/a><\/noindex> \u2014 cont\u00e9m informa\u00e7\u00f5es sobre os passageiros (idade, sexo, parentes a bordo, etc.) 891 no conjunto de treinamento e 418 \u2014 no teste.<\/li>\n<li><noindex><a rel=\"nofollow\" href=\"https:\/\/www.kaggle.com\/fivethirtyeight\/uber-pickups-in-new-york-city\">Conjunto de Dados de Coletas da Uber<\/a><\/noindex> \u2014 informa\u00e7\u00f5es sobre 4,5 milh\u00f5es de viagens da Uber em 2014 e 14 milh\u00f5es em 2015. (<i>Caso de uso com c\u00f3digo-fonte em R: <noindex><a rel=\"nofollow\" href=\"https:\/\/data-flair.training\/blogs\/r-data-science-project-uber-data-analysis\/\">Projeto de An\u00e1lise de Dados da Uber em R<\/a><\/noindex><\/i>)<\/li>\n<li><noindex><a rel=\"nofollow\" href=\"http:\/\/www.ee.surrey.ac.uk\/CVSSP\/demos\/chars74k\/\">Conjunto de Dados Chars74k<\/a><\/noindex> \u2014 cont\u00e9m imagens de s\u00edmbolos Brit\u00e2nicos e Canadenses de 64 classes: 0-9, A-Z, a-z. 7.700 imagens naturais, 3.400 escritas \u00e0 m\u00e3o, 62.000 fontes sintetizadas por computador.<\/li>\n<li><noindex><a rel=\"nofollow\" href=\"https:\/\/www.kaggle.com\/mlg-ulb\/creditcardfraud\">Conjunto de Dados de Detec\u00e7\u00e3o de Fraude com Cart\u00f5es de Cr\u00e9dito<\/a><\/noindex> \u2014 cont\u00e9m informa\u00e7\u00f5es sobre transa\u00e7\u00f5es de cart\u00f5es de cr\u00e9dito comprometidos. (<i>Caso de uso com c\u00f3digo-fonte: <noindex><a rel=\"nofollow\" href=\"https:\/\/data-flair.training\/blogs\/data-science-machine-learning-project-credit-card-fraud-detection\/\">Projeto de Detec\u00e7\u00e3o de Fraude com Cart\u00f5es de Cr\u00e9dito com Aprendizado de M\u00e1quina<\/a><\/noindex><\/i>)<\/li>\n<li><noindex><a rel=\"nofollow\" href=\"https:\/\/github.com\/katanaml\/katana-assistant\/blob\/master\/mlbackend\/intents.json\">Conjunto de Dados de Inten\u00e7\u00f5es do Chatbot<\/a><\/noindex> \u2014 arquivo JSON que cont\u00e9m v\u00e1rias tags: cumprimentos, despedidas, busca_hospital, busca_farmacia, etc. Cont\u00e9m um conjunto de modelos \"pergunta-resposta\". (<i>Caso de uso com c\u00f3digo-fonte em Python: <noindex><a rel=\"nofollow\" href=\"https:\/\/data-flair.training\/blogs\/python-chatbot-project\/\">Projeto de Chatbot em Python<\/a><\/noindex><\/i>)<\/li>\n<li><noindex><a rel=\"nofollow\" href=\"https:\/\/www.cs.cmu.edu\/~enron\/\">Conjunto de Dados de Emails da Enron<\/a><\/noindex> \u2014 cont\u00e9m meio milh\u00e3o de e-mails de 150 gerentes da Enron.<\/li>\n<li><noindex><a rel=\"nofollow\" href=\"https:\/\/www.yelp.com\/dataset\">O Conjunto de Dados do Yelp<\/a><\/noindex> \u2014 cont\u00e9m 1,2 milh\u00e3o de recomenda\u00e7\u00f5es de 1,6 milh\u00e3o de usu\u00e1rios sobre 1,2 milh\u00e3o de organiza\u00e7\u00f5es.<\/li>\n<li><noindex><a rel=\"nofollow\" href=\"https:\/\/www.reddit.com\/r\/datasets\/comments\/1uyd0t\/200000_jeopardy_questions_in_a_json_file\/\">Conjunto de Dados do Jeopardy<\/a><\/noindex> \u2014 mais de 200.000 registros \"pergunta-resposta\" do popular jogo de TV.<\/li>\n<li><noindex><a rel=\"nofollow\" href=\"https:\/\/cseweb.ucsd.edu\/~jmcauley\/datasets.html\">Conjunto de Dados de Sistemas Recomendadores<\/a><\/noindex> \u2014 portal com uma cole\u00e7\u00e3o de conjuntos de dados da Universidade UCSD. Cont\u00e9m registros de avalia\u00e7\u00f5es em sites populares (Goodreads, Amazon). Ideal para a cria\u00e7\u00e3o de sistemas de recomenda\u00e7\u00e3o. (<i>Caso de uso com c\u00f3digo-fonte em R: <noindex><a rel=\"nofollow\" href=\"https:\/\/data-flair.training\/blogs\/data-science-r-movie-recommendation\/\">Projeto de Sistema de Recomenda\u00e7\u00e3o de Filmes em R<\/a><\/noindex> <\/i>)<\/li>\n<li><noindex><a rel=\"nofollow\" href=\"https:\/\/archive.ics.uci.edu\/ml\/datasets\/Spambase\">Conjunto de Dados UCI Spambase<\/a><\/noindex> \u2014 conjunto de dados para treino na detec\u00e7\u00e3o de spam. Cont\u00e9m 4601 e-mails com 57 par\u00e2metros de metadados.<\/li>\n<li><noindex><a rel=\"nofollow\" href=\"https:\/\/www.kaggle.com\/hsankesara\/flickr-image-dataset\">Conjunto de Dados Flickr 30k<\/a><\/noindex> \u2014 mais de 30.000 imagens e legendas associadas. <i>(<noindex><a rel=\"nofollow\" href=\"https:\/\/forms.illinois.edu\/sec\/1713398\">Conjunto de Dados Flickr 8k<\/a><\/noindex> \u2014 8000 imagens. Projeto com c\u00f3digo fonte em Python: <noindex><a rel=\"nofollow\" href=\"https:\/\/data-flair.training\/blogs\/python-based-project-image-caption-generator-cnn\/\">Projeto Gerador de Legendas de Imagens em Python<\/a><\/noindex>)<\/i><\/li>\n<li><noindex><a rel=\"nofollow\" href=\"http:\/\/ai.stanford.edu\/~amaas\/data\/sentiment\/\">Avalia\u00e7\u00f5es IMDB<\/a><\/noindex> \u2014 25.000 avalia\u00e7\u00f5es de filmes no conjunto de treino e 25.000 no de teste. (<i>Caso de uso com c\u00f3digo-fonte em R: <noindex><a rel=\"nofollow\" href=\"https:\/\/data-flair.training\/blogs\/data-science-r-sentiment-analysis-project\/\">Projeto de An\u00e1lise de Sentimentos em Data Science<\/a><\/noindex><\/i>)<\/li>\n<li><noindex><a rel=\"nofollow\" href=\"http:\/\/cocodataset.org\/#home\">Conjunto de Dados MS COCO<\/a><\/noindex> \u2014 1,5 milh\u00e3o de imagens rotuladas.<\/li>\n<li><noindex><a rel=\"nofollow\" href=\"https:\/\/www.cs.toronto.edu\/~kriz\/cifar.html\">Conjunto de Dados CIFAR-10 e CIFAR-100<\/a><\/noindex> \u2014 CIFAR-10 cont\u00e9m 60.000 pequenas imagens de 32*32 pixels com os n\u00fameros de 0 a 9. CIFAR-100 \u2014 respectivamente, de 0 a 100.<\/li>\n<li><noindex><a rel=\"nofollow\" href=\"http:\/\/benchmark.ini.rub.de\/?section=gtsrb&amp;subsection=dataset\">Conjunto de Dados GTSRB (benchmark de reconhecimento de sinais de tr\u00e2nsito alem\u00e3es)<\/a><\/noindex> \u2014 50.000 imagens de 43 sinais de tr\u00e2nsito. (<i>Caso de uso com c\u00f3digo-fonte em Python: <noindex><a rel=\"nofollow\" href=\"https:\/\/data-flair.training\/blogs\/python-project-traffic-signs-recognition\/\">Projeto de Reconhecimento de Sinais de Tr\u00e2nsito em Python<\/a><\/noindex><\/i>)<\/li>\n<li><noindex><a rel=\"nofollow\" href=\"http:\/\/www.image-net.org\/\">Conjunto de Dados ImageNet<\/a><\/noindex> \u2014 cont\u00e9m mais de 100.000 frases e cerca de 1000 imagens por frase.<\/li>\n<li><noindex><a rel=\"nofollow\" href=\"https:\/\/www.kaggle.com\/paultimothymooney\/breast-histopathology-images\">Conjunto de Dados de Imagens de Histopatologia da Mama<\/a><\/noindex> \u2014 conjunto de dados cont\u00e9m imagens de amostras de c\u00e2ncer de mama. (<i>Caso de uso com c\u00f3digo fonte em <noindex><a rel=\"nofollow\" href=\"https:\/\/data-flair.training\/blogs\/project-in-python-breast-cancer-classification\/\">Projeto de Classifica\u00e7\u00e3o de C\u00e2ncer de Mama em Python<\/a><\/noindex><\/i>)<\/li>\n<li><noindex><a rel=\"nofollow\" href=\"https:\/\/www.cityscapes-dataset.com\/\">Conjunto de Dados Cityscapes<\/a><\/noindex> \u2014 cont\u00e9m anota\u00e7\u00f5es de alta qualidade de sequ\u00eancias de v\u00eddeo de ruas em diferentes cidades.<\/li>\n<li><noindex><a rel=\"nofollow\" href=\"https:\/\/deepmind.com\/research\/open-source\/kinetics\">Conjunto de Dados Kinetics<\/a><\/noindex> \u2014 cont\u00e9m um link URL para cerca de 6,5 milh\u00f5es de v\u00eddeos de alta qualidade.<\/li>\n<li><noindex><a rel=\"nofollow\" href=\"http:\/\/human-pose.mpi-inf.mpg.de\/#\">Conjunto de Dados MPII de Pose Humano<\/a><\/noindex> \u2014 conjunto de dados cont\u00e9m 25.000 imagens de poses humanas com anota\u00e7\u00f5es nas articula\u00e7\u00f5es.<\/li>\n<li><noindex><a rel=\"nofollow\" href=\"https:\/\/20bn.com\/datasets\/something-something\/v2\">Conjunto de Dados 20BN-something-something v2<\/a><\/noindex> \u2014 conjunto de v\u00eddeos de alta qualidade que mostram como uma pessoa realiza certas a\u00e7\u00f5es.<\/li>\n<li><noindex><a rel=\"nofollow\" href=\"https:\/\/www.objects365.org\/overview.html\">Conjunto de Dados Object 365<\/a><\/noindex> \u2014 conjunto de dados de imagens de alta qualidade com caixas delimitadoras de objetos.<\/li>\n<li><noindex><a rel=\"nofollow\" href=\"http:\/\/www.cs.cmu.edu\/~mengtial\/proj\/sketch\/\">Conjunto de Dados de Esbo\u00e7o de Fotos<\/a><\/noindex> \u2014 cont\u00e9m mais de 1000 imagens com seus desenhos de contorno.<\/li>\n<li><noindex><a rel=\"nofollow\" href=\"http:\/\/headctstudy.qure.ai\/#dataset\">Conjunto de Dados CQ500<\/a><\/noindex> \u2014 conjunto de dados cont\u00e9m 491 tomografias computadorizadas da cabe\u00e7a com 193.317 cortes.<\/li>\n<li><noindex><a rel=\"nofollow\" href=\"https:\/\/data.vision.ee.ethz.ch\/cvl\/rrothe\/imdb-wiki\/\">Conjunto de Dados IMDB-Wiki<\/a><\/noindex> \u2014 conjunto de dados com mais de 5 milh\u00f5es de imagens de rostos rotuladas com g\u00eanero e idade. (<i>Caso de uso com c\u00f3digo fonte em <noindex><a rel=\"nofollow\" href=\"https:\/\/data-flair.training\/blogs\/python-project-gender-age-detection\/\">Projeto de Detec\u00e7\u00e3o de G\u00eanero e Idade em Python<\/a><\/noindex><\/i>)<\/li>\n<li><noindex><a rel=\"nofollow\" href=\"https:\/\/research.google.com\/youtube8m\/\">Conjunto de Dados Youtube 8M<\/a><\/noindex> \u2014 um conjunto de dados de v\u00eddeo rotulado que cont\u00e9m 6,1 milh\u00f5es de identificadores de v\u00eddeos do Youtube.<\/li>\n<li><noindex><a rel=\"nofollow\" href=\"https:\/\/urbansounddataset.weebly.com\/urbansound8k.html\">Conjunto de Dados Urban Sound 8K<\/a><\/noindex> \u2014 um conjunto de dados de sons urbanos (cont\u00e9m 8732 sons urbanos de 10 classes).<\/li>\n<li><noindex><a rel=\"nofollow\" href=\"https:\/\/www.yf.io\/p\/lsun\">Conjunto de Dados LSUN<\/a><\/noindex> \u2014 conjunto de dados de milh\u00f5es de imagens coloridas de cenas e objetos (cerca de 59 milh\u00f5es de imagens, 10 categorias diferentes de cenas e 20 categorias diferentes de objetos).<\/li>\n<li><noindex><a rel=\"nofollow\" href=\"https:\/\/zenodo.org\/record\/1188976#.Xc-P7VczbIU\">Conjunto de Dados RAVDESS<\/a><\/noindex> \u2014 banco de dados audiovisual de fala emocional. (<i>Caso de uso com c\u00f3digo fonte em <noindex><a rel=\"nofollow\" href=\"https:\/\/data-flair.training\/blogs\/python-mini-project-speech-emotion-recognition\/\">Projeto de Reconhecimento de Emo\u00e7\u00f5es na Fala em Python<\/a><\/noindex><\/i>)<\/li>\n<li><noindex><a rel=\"nofollow\" href=\"http:\/\/www.openslr.org\/12\">Conjunto de Dados Librispeech<\/a><\/noindex> \u2014 o dataset cont\u00e9m 1000 horas de fala em ingl\u00eas com diferentes sotaques.<\/li>\n<li><noindex><a rel=\"nofollow\" href=\"http:\/\/apolloscape.auto\/\">Baidu Apolloscape Dataset<\/a><\/noindex> \u2014 dataset para o desenvolvimento de tecnologias de condu\u00e7\u00e3o aut\u00f4noma. <\/li>\n<li><noindex><a rel=\"nofollow\" href=\"https:\/\/www.quandl.com\/\">Quandl Data Portal<\/a><\/noindex> \u2014 reposit\u00f3rio de dados econ\u00f4micos e financeiros (com conte\u00fado gratuito e pago).<\/li>\n<li><noindex><a rel=\"nofollow\" href=\"https:\/\/data.worldbank.org\/\">The World Bank Open Data Portal<\/a><\/noindex> \u2014 informa\u00e7\u00f5es sobre empr\u00e9stimos concedidos pelo Banco Mundial a pa\u00edses em desenvolvimento.<\/li>\n<li><noindex><a rel=\"nofollow\" href=\"https:\/\/www.imf.org\/en\/Data\">IMF Data Portal<\/a><\/noindex> \u2014 portal do Fundo Monet\u00e1rio Internacional que publica dados sobre finan\u00e7as internacionais, taxas de d\u00edvida, investimentos, reservas cambiais e mercadorias.<\/li>\n<li><noindex><a rel=\"nofollow\" href=\"https:\/\/www.aeaweb.org\/resources\/data\">American Economic Association (AEA) Data Portal<\/a><\/noindex> \u2014 recurso para pesquisa de dados macroecon\u00f4micos dos EUA.<\/li>\n<li><noindex><a rel=\"nofollow\" href=\"https:\/\/trends.google.com\/trends\/\">Google Trends Data Portal<\/a><\/noindex> \u2014 os dados de tend\u00eancias do Google podem ser usados para visualiza\u00e7\u00e3o e an\u00e1lise de dados.<\/li>\n<li><noindex><a rel=\"nofollow\" href=\"https:\/\/markets.ft.com\/data\/\">Financial Times Market Data Portal<\/a><\/noindex> \u2014 recurso para obter informa\u00e7\u00f5es atualizadas sobre os mercados financeiros de todo o mundo.<\/li>\n<li><noindex><a rel=\"nofollow\" href=\"https:\/\/www.data.gov\/\">Data.gov Portal<\/a><\/noindex> \u2014 portal de dados abertos do governo dos EUA (agricultura, sa\u00fade, clima, educa\u00e7\u00e3o, energia, finan\u00e7as, ci\u00eancia e pesquisa, etc.).<\/li>\n<li><noindex><a rel=\"nofollow\" href=\"https:\/\/data.gov.in\/\">Data Portal: Open government data (India)<\/a><\/noindex> \u2014 plataforma de dados abertos do governo da \u00cdndia.<\/li>\n<li><noindex><a rel=\"nofollow\" href=\"https:\/\/catalog.data.gov\/dataset\/food-environment-atlas-f4a22\">Food environment Atlas Data Portal<\/a><\/noindex> \u2014 cont\u00e9m dados de pesquisas sobre nutri\u00e7\u00e3o nos EUA.<\/li>\n<li><noindex><a rel=\"nofollow\" href=\"https:\/\/healthdata.gov\/\">Health Data Portal<\/a><\/noindex> \u2014 este \u00e9 o portal do Departamento de Sa\u00fade e Servi\u00e7os Humanos dos EUA.<\/li>\n<li><noindex><a rel=\"nofollow\" href=\"https:\/\/www.cdc.gov\/datastatistics\/\">Centers for Disease Control and Prevention Data Portal<\/a><\/noindex> \u2014 cont\u00e9m uma ampla gama de dados relacionados \u00e0 sa\u00fade.<\/li>\n<li><noindex><a rel=\"nofollow\" href=\"https:\/\/data.london.gov.uk\/\">London Datastore Portal<\/a><\/noindex> \u2014 dados sobre a vida das pessoas em Londres.<\/li>\n<li><noindex><a rel=\"nofollow\" href=\"https:\/\/open.canada.ca\/en\/open-data\">Canada Government Open Data Portal<\/a><\/noindex> \u2014 portal de dados abertos sobre canadenses (agricultura, arte, m\u00fasica, educa\u00e7\u00e3o, governo, sa\u00fade, etc.)<\/li>\n<\/ol>\n<h3>Leia mais<\/h3>\n<p><\/p>\n<ul>\n<li><noindex><a rel=\"nofollow\" href=\"https:\/\/habr.com\/ru\/company\/edison\/blog\/480378\/\">14 projetos open-source para melhorar suas habilidades em Data Science (f\u00e1cil, normal, dif\u00edcil)<\/a><\/noindex><\/li>\n<li><noindex><a rel=\"nofollow\" href=\"https:\/\/habr.com\/ru\/company\/edison\/blog\/479100\/\">Front-end do dojo: projetos para treinar habilidades de desenvolvedor (5 novos + 43 antigos)<\/a><\/noindex><\/li>\n<li><noindex><a rel=\"nofollow\" href=\"https:\/\/habr.com\/ru\/company\/edison\/blog\/479650\/\">Top 12 das infogr\u00e1ficos din\u00e2micos de TI mais interessantes<\/a><\/noindex><\/li>\n<\/ul>\n<p>Fonte: <a content=\"nofollow\" rel=\"nofollow\" href=\"https:\/\/habr.com\/ru\/company\/edison\/blog\/480408\/\">habr.com<\/a><\/p>","protected":false,"gt_translate_keys":[{"key":"rendered","format":"html"}]},"excerpt":{"rendered":"<p>Mall Customers Dataset \u2014 \u0434\u0430\u043d\u043d\u044b\u0435 \u043f\u043e\u0441\u0435\u0442\u0438\u0442\u0435\u043b\u0435\u0439 \u043c\u0430\u0433\u0430\u0437\u0438\u043d\u0430: id, \u043f\u043e\u043b, \u0432\u043e\u0437\u0440\u0430\u0441\u0442, \u0434\u043e\u0445\u043e\u0434, \u0440\u0435\u0439\u0442\u0438\u043d\u0433 \u0442\u0440\u0430\u0442. (\u0412\u0430\u0440\u0438\u0430\u043d\u0442 \u043f\u0440\u0438\u043c\u0435\u043d\u0435\u043d\u0438\u044f: Customer Segmentation Project with Machine Learning) Iris Dataset \u2014 \u0434\u0430\u0442\u0430\u0441\u0435\u0442 \u0434\u043b\u044f \u043d\u043e\u0432\u0438\u0447\u043a\u043e\u0432, \u0441\u043e\u0434\u0435\u0440\u0436\u0430\u0449\u0438\u0439 \u0440\u0430\u0437\u043c\u0435\u0440\u044b \u0447\u0430\u0448\u0435\u043b\u0438\u0441\u0442\u0438\u043a\u043e\u0432 \u0438 \u043b\u0435\u043f\u0435\u0441\u0442\u043a\u043e\u0432 \u0434\u043b\u044f \u0440\u0430\u0437\u043b\u0438\u0447\u043d\u044b\u0445 \u0446\u0432\u0435\u0442\u043a\u043e\u0432. MNIST Dataset \u2014 \u0434\u0430\u0442\u0430\u0441\u0435\u0442 \u0440\u0443\u043a\u043e\u043f\u0438\u0441\u043d\u044b\u0445 \u0446\u0438\u0444\u0440. 60 000 \u0442\u0440\u0435\u043d\u0438\u0440\u043e\u0432\u043e\u0447\u043d\u044b\u0445 \u0438\u0437\u043e\u0431\u0440\u0430\u0436\u0435\u043d\u0438\u0439 \u0438 10 000 \u0442\u0435\u0441\u0442\u043e\u0432\u044b\u0445 \u0438\u0437\u043e\u0431\u0440\u0430\u0436\u0435\u043d\u0438\u0439. The Boston Housing Dataset \u2014 [&hellip;]<\/p>\n","protected":false,"gt_translate_keys":[{"key":"rendered","format":"html"}]},"author":1,"featured_media":54097,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[702],"tags":[],"class_list":["post-54096","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-news"],"aioseo_notices":[],"aioseo_head":"\n\t\t<!-- All in One SEO 5.0.3 - aioseo.com -->\n\t<meta name=\"description\" content=\"Mall Customers Dataset \u2014 \u0434\u0430\u043d\u043d\u044b\u0435 \u043f\u043e\u0441\u0435\u0442\u0438\u0442\u0435\u043b\u0435\u0439 \u043c\u0430\u0433\u0430\u0437\u0438\u043d\u0430: id, \u043f\u043e\u043b, \u0432\u043e\u0437\u0440\u0430\u0441\u0442, \u0434\u043e\u0445\u043e\u0434, \u0440\u0435\u0439\u0442\u0438\u043d\u0433 \u0442\u0440\u0430\u0442.\" \/>\n\t<meta name=\"robots\" content=\"max-image-preview:large\" \/>\n\t<meta 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