{"id":10796,"date":"2024-05-19T04:17:54","date_gmt":"2024-05-19T01:17:54","guid":{"rendered":"https:\/\/sunucun.com.tr\/bilgi\/?post_type=dt_articles&#038;p=10796"},"modified":"2026-02-06T22:11:39","modified_gmt":"2026-02-06T19:11:39","slug":"aws-sagemaker-nedir-neden","status":"publish","type":"post","link":"https:\/\/sunucun.com.tr\/blog\/aws-sagemaker-nedir-neden\/","title":{"rendered":"Aws SageMaker Nedir 2 Ad\u0131mda G\u00f6sterim"},"content":{"rendered":"<div id=\"ez-toc-container\" class=\"ez-toc-v2_0_84 ez-toc-wrap-center counter-hierarchy ez-toc-counter ez-toc-custom ez-toc-container-direction\">\n<div class=\"ez-toc-title-container\">\n<span class=\"ez-toc-title-toggle\"><\/span><\/div>\n<nav><ul class='ez-toc-list ez-toc-list-level-1 ' ><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-1\" href=\"https:\/\/sunucun.com.tr\/blog\/aws-sagemaker-nedir-neden\/#Amazon_SageMaker_AWSnin_Kapsamli_Makine_Ogrenimi_Hizmeti\" >Amazon SageMaker: AWS&#8217;nin Kapsaml\u0131 Makine \u00d6\u011frenimi Hizmeti<\/a><ul class='ez-toc-list-level-3' ><li class='ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-2\" href=\"https:\/\/sunucun.com.tr\/blog\/aws-sagemaker-nedir-neden\/#Neden_Amazon_SageMaker_Kullanilmali\" >Neden Amazon SageMaker Kullan\u0131lmal\u0131?<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-3\" href=\"https:\/\/sunucun.com.tr\/blog\/aws-sagemaker-nedir-neden\/#Amazon_SageMaker_Nasil_Kullanilir\" >Amazon SageMaker Nas\u0131l Kullan\u0131l\u0131r?<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-4\" href=\"https:\/\/sunucun.com.tr\/blog\/aws-sagemaker-nedir-neden\/#Amazon_SageMaker_Bilesenleri\" >Amazon SageMaker Bile\u015fenleri<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-5\" href=\"https:\/\/sunucun.com.tr\/blog\/aws-sagemaker-nedir-neden\/#Amazon_SageMakerin_Onemi\" >Amazon SageMaker&#8217;\u0131n \u00d6nemi<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-6\" href=\"https:\/\/sunucun.com.tr\/blog\/aws-sagemaker-nedir-neden\/#Sonuc\" >Sonu\u00e7<\/a><\/li><\/ul><\/li><\/ul><\/nav><\/div>\n<h2><span class=\"ez-toc-section\" id=\"Amazon_SageMaker_AWSnin_Kapsamli_Makine_Ogrenimi_Hizmeti\"><\/span>Amazon SageMaker: AWS&#8217;nin Kapsaml\u0131 Makine \u00d6\u011frenimi Hizmeti<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>Amazon SageMaker, Amazon Web Services (AWS) taraf\u0131ndan sa\u011flanan, veri bilimciler ve geli\u015ftiriciler i\u00e7in makine \u00f6\u011frenimi (ML) modelleri olu\u015fturmay\u0131, e\u011fitmeyi ve da\u011f\u0131tmay\u0131 kolayla\u015ft\u0131ran tamamen y\u00f6netilen bir hizmettir. SageMaker, ML geli\u015ftirme s\u00fcrecini basitle\u015ftirir ve veri haz\u0131rlama, algoritma se\u00e7imi, model e\u011fitimi ve da\u011f\u0131t\u0131m\u0131 gibi ad\u0131mlar\u0131 optimize eder. Bu \u00f6zellikleri sayesinde, SageMaker, makine \u00f6\u011frenimi s\u00fcre\u00e7lerini h\u0131zland\u0131rarak verimlili\u011fi art\u0131r\u0131r.<\/p>\n<h3><span class=\"ez-toc-section\" id=\"Neden_Amazon_SageMaker_Kullanilmali\"><\/span>Neden Amazon SageMaker Kullan\u0131lmal\u0131?<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p><strong>U\u00e7tan Uca ML \u0130\u015f Ak\u0131\u015f\u0131:<\/strong> SageMaker, veri haz\u0131rlama, model olu\u015fturma, e\u011fitim, ayarlama ve da\u011f\u0131t\u0131m\u0131 i\u00e7eren t\u00fcm makine \u00f6\u011frenimi ya\u015fam d\u00f6ng\u00fcs\u00fcn\u00fc destekler. Bu u\u00e7tan uca destek, karma\u015f\u0131k ML s\u00fcre\u00e7lerini basitle\u015ftirir. Kullan\u0131c\u0131lar, t\u00fcm bu ad\u0131mlar\u0131 tek bir platformda ger\u00e7ekle\u015ftirerek zaman ve maliyet tasarrufu sa\u011flar.<\/p>\n<p><strong>\u00d6l\u00e7eklenebilirlik:<\/strong> SageMaker, b\u00fcy\u00fck veri setlerini ve karma\u015f\u0131k modelleri verimli bir \u015fekilde e\u011fitmek ve \u00e7\u0131kar\u0131m yapmak i\u00e7in kolayca \u00f6l\u00e7eklenebilir. Bu, y\u00fcksek performans gerektiren ML uygulamalar\u0131 i\u00e7in idealdir.<\/p>\n<p><strong>Y\u00f6netilen Altyap\u0131:<\/strong> AWS, altyap\u0131y\u0131 y\u00f6netir, bu nedenle kullan\u0131c\u0131lar sunucular\u0131, depolama ve a\u011f kaynaklar\u0131n\u0131 sa\u011flama ve bak\u0131m yapma konusunda endi\u015felenmek zorunda kalmazlar. Bu, kullan\u0131c\u0131lar\u0131n sadece model geli\u015ftirmeye odaklanmas\u0131na olanak tan\u0131r.<\/p>\n<p><strong>Entegre Ara\u00e7lar:<\/strong> SageMaker, veri etiketleme, \u00f6zellik m\u00fchendisli\u011fi, algoritma se\u00e7imi ve hiperparametre ayarlama gibi y\u00fcksek kaliteli modeller geli\u015ftirmeyi kolayla\u015ft\u0131ran yerle\u015fik ara\u00e7lar sunar. Bu ara\u00e7lar, kullan\u0131c\u0131lar\u0131n modellerini optimize etmelerini ve en iyi sonu\u00e7lar\u0131 elde etmelerini sa\u011flar.<\/p>\n<p><strong>Maliyet Verimlili\u011fi:<\/strong> SageMaker&#8217;\u0131n kulland\u0131k\u00e7a \u00f6de fiyatland\u0131rma modeli ve kaynak optimizasyon \u00f6zellikleri, maliyetleri kontrol etmeye yard\u0131mc\u0131 olurken y\u00fcksek performans sa\u011flar. Bu, i\u015fletmelerin ML projelerini ekonomik bir \u015fekilde y\u00fcr\u00fctmelerine olanak tan\u0131r.<\/p>\n<h3><span class=\"ez-toc-section\" id=\"Amazon_SageMaker_Nasil_Kullanilir\"><\/span>Amazon SageMaker Nas\u0131l Kullan\u0131l\u0131r?<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p><strong>Veri Haz\u0131rlama:<\/strong> SageMaker Data Wrangler kullanarak verilerinizi temizleyin, d\u00f6n\u00fc\u015ft\u00fcr\u00fcn ve ke\u015ffedin. Bu ara\u00e7, makine \u00f6\u011frenimi i\u00e7in veri haz\u0131rlama s\u00fcrecini basitle\u015ftirir. Verilerinizi h\u0131zl\u0131 ve etkili bir \u015fekilde haz\u0131rlamak, model performans\u0131n\u0131 do\u011frudan etkiler.<\/p>\n<p><strong>Modelleri Olu\u015fturma:<\/strong> SageMaker Studio veya Jupyter defterlerini kullanarak ML modelleri olu\u015fturun ve deney yap\u0131n. SageMaker, TensorFlow, PyTorch ve MXNet gibi bir\u00e7ok ML \u00e7er\u00e7evesini ve yerle\u015fik algoritmalar\u0131 destekler. Bu esneklik, farkl\u0131 ML projeleri i\u00e7in uygun \u00e7\u00f6z\u00fcmler sunar.<\/p>\n<p><strong>Modelleri E\u011fitme:<\/strong> SageMaker&#8217;\u0131n y\u00f6netilen altyap\u0131s\u0131n\u0131 kullanarak modelleri e\u011fitin. Da\u011f\u0131t\u0131lm\u0131\u015f e\u011fitim ve otomatik model ayarlama \u00f6zelliklerinden yararlanarak modellerin performans\u0131n\u0131 optimize edin. Bu, \u00f6zellikle b\u00fcy\u00fck veri setleriyle \u00e7al\u0131\u015fan projeler i\u00e7in kritiktir.<\/p>\n<p><strong>Modelleri Da\u011f\u0131tma:<\/strong> SageMaker&#8217;\u0131n bar\u0131nd\u0131rma hizmetlerini kullanarak ger\u00e7ek zamanl\u0131 \u00e7\u0131kar\u0131m veya toplu i\u015fleme i\u00e7in e\u011fitilen modelleri da\u011f\u0131t\u0131n. SageMaker, u\u00e7 noktalar olu\u015fturmay\u0131 ve model da\u011f\u0131t\u0131m\u0131 i\u00e7in A\/B testlerini y\u00f6netmeyi kolayla\u015ft\u0131r\u0131r. Bu, model performans\u0131n\u0131 ger\u00e7ek d\u00fcnyada test etmek i\u00e7in \u00f6nemlidir.<\/p>\n<p><strong>Modelleri \u0130zleme ve Y\u00f6netme:<\/strong> SageMaker Model Monitor kullanarak model performans\u0131n\u0131 s\u00fcrekli izleyin, veri sapmalar\u0131n\u0131 tespit edin ve modellerin do\u011frulu\u011funu ve g\u00fcvenilirli\u011fini koruyun. Bu, modellerin zaman i\u00e7inde performanslar\u0131n\u0131 korumas\u0131 i\u00e7in gereklidir.<\/p>\n<h3><span class=\"ez-toc-section\" id=\"Amazon_SageMaker_Bilesenleri\"><\/span>Amazon SageMaker Bile\u015fenleri<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p><strong>SageMaker Studio:<\/strong> ML modelleri olu\u015fturmak, e\u011fitmek ve da\u011f\u0131tmak i\u00e7in web tabanl\u0131 bir aray\u00fcz sunan entegre bir geli\u015ftirme ortam\u0131 (IDE). Kullan\u0131c\u0131lar, t\u00fcm ML s\u00fcrecini tek bir yerden y\u00f6netebilirler.<\/p>\n<p><strong>SageMaker Defterleri:<\/strong> Etkile\u015fimli geli\u015ftirme ve deney yapmay\u0131 kolayla\u015ft\u0131ran y\u00f6netilen Jupyter defterleri. Bu defterler, veri bilimcilerinin \u00e7al\u0131\u015fmalar\u0131n\u0131 daha verimli bir \u015fekilde y\u00fcr\u00fctmelerine yard\u0131mc\u0131 olur.<\/p>\n<p><strong>SageMaker Data Wrangler:<\/strong> Veri setlerini temizleme, d\u00f6n\u00fc\u015ft\u00fcrme ve g\u00f6rselle\u015ftirme dahil olmak \u00fczere veri haz\u0131rlama ve i\u015fleme arac\u0131. Bu ara\u00e7, veri haz\u0131rl\u0131k s\u00fcrecini h\u0131zland\u0131r\u0131r ve hata olas\u0131l\u0131\u011f\u0131n\u0131 azalt\u0131r.<\/p>\n<p><strong>SageMaker Training:<\/strong> AWS altyap\u0131s\u0131nda ML modellerini e\u011fitmek i\u00e7in <a href=\"https:\/\/sunucun.com.tr\/sunucu-bakimi\" data-internallinksmanager029f6b8e52c=\"88\" title=\"Sunucu bak\u0131m ve y\u00f6netim hizmeti\">y\u00f6netilen hizmet<\/a>, da\u011f\u0131t\u0131lm\u0131\u015f e\u011fitim ve hiperparametre optimizasyonunu destekler. Bu, daha b\u00fcy\u00fck ve karma\u015f\u0131k modellerin e\u011fitilmesini m\u00fcmk\u00fcn k\u0131lar.<\/p>\n<p><strong>SageMaker Inference:<\/strong> Ger\u00e7ek zamanl\u0131 \u00e7\u0131kar\u0131m (bar\u0131nd\u0131rma u\u00e7 noktalar\u0131) ve toplu \u00e7\u0131kar\u0131m i\u00e7in ML modellerini da\u011f\u0131tma hizmetleri. Bu \u00f6zellik, modellerin geni\u015f \u00f6l\u00e7ekte kullan\u0131lmas\u0131na olanak tan\u0131r.<\/p>\n<p><strong>SageMaker Model Monitor:<\/strong> Da\u011f\u0131t\u0131lan modelleri izleme, performanslar\u0131n\u0131 takip etme ve anormallikleri veya veri kalitesi sorunlar\u0131n\u0131 tespit etme arac\u0131. Bu, modellerin uzun vadede g\u00fcvenilirli\u011fini sa\u011flar.<\/p>\n<p><strong>SageMaker Autopilot:<\/strong> Derin ML bilgisi gerektirmeden en iyi ML modelini otomatik olarak olu\u015fturan otomatik makine \u00f6\u011frenimi (AutoML) arac\u0131. Bu ara\u00e7, kullan\u0131c\u0131lar\u0131n ML modelleri olu\u015fturmas\u0131n\u0131 kolayla\u015ft\u0131r\u0131r.<\/p>\n<h3><span class=\"ez-toc-section\" id=\"Amazon_SageMakerin_Onemi\"><\/span>Amazon SageMaker&#8217;\u0131n \u00d6nemi<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p><strong>ML Geli\u015ftirmesini Basitle\u015ftirir:<\/strong> U\u00e7tan uca bir \u00e7\u00f6z\u00fcm sunarak, ML modelleri geli\u015ftirme ve da\u011f\u0131tma s\u00fcrecini basitle\u015ftirir ve h\u0131zland\u0131r\u0131r. Bu, i\u015fletmelerin ML projelerini daha h\u0131zl\u0131 hayata ge\u00e7irmelerine olanak tan\u0131r.<\/p>\n<p><strong>Pazara H\u0131zl\u0131 \u00c7\u0131k\u0131\u015f:<\/strong> Entegre i\u015f ak\u0131\u015flar\u0131 ve ara\u00e7lar, ekiplerin modelleri daha h\u0131zl\u0131 geli\u015ftirmesine ve da\u011f\u0131tmas\u0131na yard\u0131mc\u0131 olarak pazara \u00e7\u0131k\u0131\u015f s\u00fcresini h\u0131zland\u0131r\u0131r.<\/p>\n<p><strong>\u0130\u015fbirli\u011fini Art\u0131r\u0131r:<\/strong> SageMaker Studio ve Defterler gibi ara\u00e7lar, veri bilimciler, geli\u015ftiriciler ve i\u015f payda\u015flar\u0131 aras\u0131nda i\u015fbirli\u011fini kolayla\u015ft\u0131r\u0131r. Bu, projelerin daha verimli bir \u015fekilde y\u00f6netilmesini sa\u011flar.<\/p>\n<p><strong>Performans\u0131 Optimize Eder:<\/strong> Otomatik model ayarlama ve da\u011f\u0131t\u0131lm\u0131\u015f e\u011fitim \u00f6zellikleri, modellerin performans\u0131n\u0131 ve \u00f6l\u00e7eklenebilirli\u011fini optimize eder. Bu, daha iyi ve daha do\u011fru sonu\u00e7lar elde edilmesine yard\u0131mc\u0131 olur.<\/p>\n<p><strong>G\u00fcvenilirlik Sa\u011flar:<\/strong> Y\u00f6netilen hizmetler ve s\u00fcrekli izleme ara\u00e7lar\u0131, \u00fcretimdeki ML modellerinin tutarl\u0131 performans ve g\u00fcvenilirli\u011fini korumas\u0131na yard\u0131mc\u0131 olur. Bu da, uzun vadede ba\u015far\u0131l\u0131 projeler i\u00e7in kritiktir.<\/p>\n<h3><span class=\"ez-toc-section\" id=\"Sonuc\"><\/span>Sonu\u00e7<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p>Amazon SageMaker, makine \u00f6\u011frenimi s\u00fcrecini u\u00e7tan uca basitle\u015ftiren g\u00fc\u00e7l\u00fc ve esnek bir hizmettir. Veri haz\u0131rlamadan model da\u011f\u0131t\u0131m\u0131na ve izlemeye kadar, SageMaker t\u00fcm ML ya\u015fam d\u00f6ng\u00fcs\u00fcn\u00fc kapsayan entegre ara\u00e7lar ve altyap\u0131 sa\u011flar. AWS ekosistemine entegrasyonu, \u00f6l\u00e7eklenebilirli\u011fi ve maliyet verimlili\u011fi ile SageMaker, modern ML i\u015f ak\u0131\u015flar\u0131 i\u00e7in temel bir platformdur.<\/p>\n<p>Daha fazla bilgi i\u00e7in resmi sayfay\u0131 ziyaret edebilirsiniz: <a href=\"https:\/\/www.sunucun.com.tr\/blog\/dt-articles\/aws-sagemaker-nedir-neden\/\">Amazon SageMaker: AWS&#8217;nin Kapsaml\u0131 Makine \u00d6\u011frenimi Hizmeti<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Amazon SageMaker: AWS&#8217;nin Kapsaml\u0131 Makine \u00d6\u011frenimi Hizmeti Amazon SageMaker, Amazon Web Services (AWS) taraf\u0131ndan sa\u011flanan, veri bilimciler ve geli\u015ftiriciler i\u00e7in makine \u00f6\u011frenimi (ML) modelleri olu\u015fturmay\u0131, e\u011fitmeyi ve da\u011f\u0131tmay\u0131 kolayla\u015ft\u0131ran tamamen y\u00f6netilen bir hizmettir. SageMaker, ML geli\u015ftirme s\u00fcrecini basitle\u015ftirir ve veri haz\u0131rlama, algoritma se\u00e7imi, model e\u011fitimi ve da\u011f\u0131t\u0131m\u0131 gibi ad\u0131mlar\u0131 optimize eder. Bu \u00f6zellikleri sayesinde, SageMaker,&hellip;<\/p>\n","protected":false},"author":1,"featured_media":10709,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_uf_show_specific_survey":0,"_uf_disable_surveys":false,"footnotes":""},"categories":[1521],"tags":[1527],"class_list":["post-10796","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-teknoloji","tag-teknoloji"],"_links":{"self":[{"href":"https:\/\/sunucun.com.tr\/blog\/wp-json\/wp\/v2\/posts\/10796","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/sunucun.com.tr\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/sunucun.com.tr\/blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/sunucun.com.tr\/blog\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/sunucun.com.tr\/blog\/wp-json\/wp\/v2\/comments?post=10796"}],"version-history":[{"count":1,"href":"https:\/\/sunucun.com.tr\/blog\/wp-json\/wp\/v2\/posts\/10796\/revisions"}],"predecessor-version":[{"id":20027,"href":"https:\/\/sunucun.com.tr\/blog\/wp-json\/wp\/v2\/posts\/10796\/revisions\/20027"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/sunucun.com.tr\/blog\/wp-json\/wp\/v2\/media\/10709"}],"wp:attachment":[{"href":"https:\/\/sunucun.com.tr\/blog\/wp-json\/wp\/v2\/media?parent=10796"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/sunucun.com.tr\/blog\/wp-json\/wp\/v2\/categories?post=10796"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/sunucun.com.tr\/blog\/wp-json\/wp\/v2\/tags?post=10796"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}