{"id":801,"date":"2026-08-18T20:03:33","date_gmt":"2026-08-18T17:03:33","guid":{"rendered":"https:\/\/www.tayfnews.tech\/tr\/genel\/nvidia-coklu-gpu-destekli-umap-ile-buyuk-verileri-hizlandiriyor\/"},"modified":"2026-08-18T20:03:33","modified_gmt":"2026-08-18T17:03:33","slug":"nvidia-coklu-gpu-destekli-umap-ile-buyuk-verileri-hizlandiriyor","status":"publish","type":"post","link":"https:\/\/www.tayfnews.tech\/tr\/technology\/nvidia-coklu-gpu-destekli-umap-ile-buyuk-verileri-hizlandiriyor\/","title":{"rendered":"Nvidia, \u00c7oklu GPU Destekli UMAP ile B\u00fcy\u00fck Verileri H\u0131zland\u0131r\u0131yor"},"content":{"rendered":"<p>Nvidia, Uniform Manifold Approximation and Projection algoritmalar\u0131n\u0131 h\u0131zland\u0131rmak i\u00e7in A\u011fustos 2026&#8217;da y\u00fcksek performansl\u0131 bir \u00e7oklu GPU bili\u015fim y\u00f6ntemi yay\u0131nlad\u0131. Bu \u00e7\u0131\u011f\u0131r a\u00e7an geli\u015fme, veri bilimcilerinin da\u011f\u0131t\u0131k donan\u0131m k\u00fcmelerinde matematiksel hassasiyeti korurken devasa veri setlerini dakikalar i\u00e7inde i\u015flemesini sa\u011fl\u0131yor. Tarihsel bellek darbo\u011fazlar\u0131n\u0131 \u00e7\u00f6zen mimari, kurumsal hatlar\u0131n a\u015f\u0131r\u0131 veri \u00f6l\u00e7eklerini ele alma bi\u00e7imini d\u00f6n\u00fc\u015ft\u00fcr\u00fcyor.<\/p>\n<p>Y\u00fcksek boyutlu veri g\u00f6rselle\u015ftirme, modern kurumsal analitik ortamlar\u0131nda genellikle b\u00fcy\u00fck hesaplama darbo\u011fazlar\u0131 yarat\u0131r. Geleneksel tek i\u015flemcili hatlar, performans ciddi \u015fekilde d\u00fc\u015fmeden milyarlarca y\u00fcksek boyutlu vekt\u00f6r i\u00e7eren veri setlerini i\u015flemekte zorlan\u0131r. Bu mimari s\u0131n\u0131rlama, m\u00fchendislik ekiplerinin ke\u015fifsel veri analizi s\u0131ras\u0131nda i\u015flem h\u0131z\u0131 ile uzamsal do\u011fruluk aras\u0131nda uzla\u015fma yapmaya zorlar ve k\u00fcresel teknoloji sekt\u00f6rlerinde ara\u015ft\u0131rma hatlar\u0131n\u0131 yava\u015flat\u0131r.<\/p>\n<div id=\"ez-toc-container\" class=\"ez-toc-v2_0_86 counter-hierarchy ez-toc-counter ez-toc-transparent ez-toc-container-direction\">\n<div class=\"ez-toc-title-container\">\n<p class=\"ez-toc-title\" style=\"cursor:inherit\">\u0130\u00e7indekiler<\/p>\n<span class=\"ez-toc-title-toggle\"><a href=\"#\" class=\"ez-toc-pull-right ez-toc-btn ez-toc-btn-xs ez-toc-btn-default ez-toc-toggle\" aria-label=\"\u0130\u00e7indekiler Tablosunu A\u00e7\/Kapat\"><span class=\"ez-toc-js-icon-con\"><span class=\"\"><span class=\"eztoc-hide\" style=\"display:none;\">Toggle<\/span><span class=\"ez-toc-icon-toggle-span\"><svg style=\"fill: #999;color:#999\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" class=\"list-377408\" width=\"20px\" height=\"20px\" viewBox=\"0 0 24 24\" fill=\"none\"><path d=\"M6 6H4v2h2V6zm14 0H8v2h12V6zM4 11h2v2H4v-2zm16 0H8v2h12v-2zM4 16h2v2H4v-2zm16 0H8v2h12v-2z\" fill=\"currentColor\"><\/path><\/svg><svg style=\"fill: #999;color:#999\" class=\"arrow-unsorted-368013\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" width=\"10px\" height=\"10px\" viewBox=\"0 0 24 24\" version=\"1.2\" baseProfile=\"tiny\"><path d=\"M18.2 9.3l-6.2-6.3-6.2 6.3c-.2.2-.3.4-.3.7s.1.5.3.7c.2.2.4.3.7.3h11c.3 0 .5-.1.7-.3.2-.2.3-.5.3-.7s-.1-.5-.3-.7zM5.8 14.7l6.2 6.3 6.2-6.3c.2-.2.3-.5.3-.7s-.1-.5-.3-.7c-.2-.2-.4-.3-.7-.3h-11c-.3 0-.5.1-.7.3-.2.2-.3.5-.3.7s.1.5.3.7z\"\/><\/svg><\/span><\/span><\/span><\/a><\/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:\/\/www.tayfnews.tech\/tr\/technology\/nvidia-coklu-gpu-destekli-umap-ile-buyuk-verileri-hizlandiriyor\/#Temel_Gercekler\" >Temel Ger\u00e7ekler<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-2\" href=\"https:\/\/www.tayfnews.tech\/tr\/technology\/nvidia-coklu-gpu-destekli-umap-ile-buyuk-verileri-hizlandiriyor\/#Hesaplama_Darbogazlarinin_Ustesinden_Gelmek\" >Hesaplama Darbo\u011fazlar\u0131n\u0131n \u00dcstesinden Gelmek<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-3\" href=\"https:\/\/www.tayfnews.tech\/tr\/technology\/nvidia-coklu-gpu-destekli-umap-ile-buyuk-verileri-hizlandiriyor\/#Tarihsel_Baglam_ve_Evrim\" >Tarihsel Ba\u011flam ve Evrim<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-4\" href=\"https:\/\/www.tayfnews.tech\/tr\/technology\/nvidia-coklu-gpu-destekli-umap-ile-buyuk-verileri-hizlandiriyor\/#Pazar_Etkisi_ve_Kurumsal_Uygulamalar\" >Pazar Etkisi ve Kurumsal Uygulamalar<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-5\" href=\"https:\/\/www.tayfnews.tech\/tr\/technology\/nvidia-coklu-gpu-destekli-umap-ile-buyuk-verileri-hizlandiriyor\/#Teknik_Uygulama_Gerceklikleri\" >Teknik Uygulama Ger\u00e7eklikleri<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-6\" href=\"https:\/\/www.tayfnews.tech\/tr\/technology\/nvidia-coklu-gpu-destekli-umap-ile-buyuk-verileri-hizlandiriyor\/#Paydas_Analizi_ve_Gelecek_Etkileri\" >Payda\u015f Analizi ve Gelecek Etkileri<\/a><\/li><\/ul><\/nav><\/div>\n<h2><span class=\"ez-toc-section\" id=\"Temel_Gercekler\"><\/span>Temel Ger\u00e7ekler<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<ul>\n<li><strong>\u0130\u015flem H\u0131z\u0131:<\/strong> Devasa \u00f6l\u00e7ekli boyutsall\u0131k indirgeme i\u015f ak\u0131\u015flar\u0131n\u0131 saatler yerine dakikalar i\u00e7inde y\u00fcr\u00fct\u00fcr.<\/li>\n<li><strong>Donan\u0131m Entegrasyonu:<\/strong> Hesaplama i\u015f y\u00fcklerini dinamik olarak dengelemek i\u00e7in da\u011f\u0131t\u0131k \u00e7oklu GPU altyap\u0131lar\u0131ndan yararlan\u0131r.<\/li>\n<li><strong>Do\u011fruluk Koruma:<\/strong> GPU d\u00fc\u011f\u00fcmleri aras\u0131nda yakla\u015f\u0131m sapmas\u0131 yaratmadan kat\u0131 matematiksel sadakati korur.<\/li>\n<li><strong>\u0130\u015f Ak\u0131\u015f\u0131 Uygulamas\u0131:<\/strong> Tek h\u00fccreli genomik, konu modelleme ve ke\u015fifsel veri analizi dahil yinelemeli g\u00f6revleri optimize eder.<\/li>\n<\/ul>\n<h2><span class=\"ez-toc-section\" id=\"Hesaplama_Darbogazlarinin_Ustesinden_Gelmek\"><\/span>Hesaplama Darbo\u011fazlar\u0131n\u0131n \u00dcstesinden Gelmek<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>Boyutsall\u0131k indirgeme, karma\u015f\u0131k, \u00e7ok de\u011fi\u015fkenli bilgileri insan g\u00f6rselle\u015ftirmesi ve makine \u00f6\u011frenimi al\u0131m\u0131 i\u00e7in d\u00fc\u015f\u00fck boyutlu uzaylara haritaland\u0131r\u0131r. UMAP gibi algoritmalar, bu yap\u0131lar\u0131n d\u00fc\u015f\u00fck boyutlu temsillerini olu\u015fturmadan \u00f6nce y\u00fcksek boyutlu kom\u015fu grafikleri hesaplar. Tek cihazl\u0131 bellek s\u0131n\u0131rlar\u0131, geleneksel olarak m\u00fchendislerin ayn\u0131 anda ne kadar veriyi analiz edebilece\u011fini k\u0131s\u0131tl\u0131yordu. Da\u011f\u0131t\u0131k \u00e7oklu GPU y\u00fcr\u00fctme, veri setini birden fazla h\u0131zland\u0131r\u0131c\u0131 aras\u0131nda b\u00f6lerek bu fiziksel bellek s\u0131n\u0131rlar\u0131n\u0131 a\u015far.<\/p>\n<p>Ayr\u0131 i\u015flemciler aras\u0131nda paralel hesaplamalar\u0131 koordine etmek, \u00f6nemli ileti\u015fim ek y\u00fck\u00fc ve senkronizasyon zorluklar\u0131 ortaya \u00e7\u0131kar\u0131r. D\u00fc\u011f\u00fcm noktalar\u0131 grafik ba\u011flant\u0131 verilerini verimsiz bir \u015fekilde takas ederse, ortaya \u00e7\u0131kan g\u00f6mme yap\u0131sal bozulmadan muzdarip olur. Yeni \u00e7oklu GPU yakla\u015f\u0131m\u0131, k\u00fcresel ba\u011flant\u0131 metriklerini korumak i\u00e7in veri aktar\u0131m protokollerini optimize eder. M\u00fchendisler, do\u011fru analiz i\u00e7in gerekli olan ince taneli yerel mahalle yap\u0131lar\u0131ndan \u00f6d\u00fcn vermeden do\u011frusal \u00f6l\u00e7eklendirme avantajlar\u0131 elde eder.<\/p>\n<h2><span class=\"ez-toc-section\" id=\"Tarihsel_Baglam_ve_Evrim\"><\/span>Tarihsel Ba\u011flam ve Evrim<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>Boyutsall\u0131k indirgeme ara\u00e7lar\u0131n\u0131n evrimi uzun s\u00fcredir fiziksel bellek s\u0131n\u0131rlar\u0131yla k\u0131s\u0131tlanm\u0131\u015ft\u0131r. Erken d\u00f6nem algoritmalar tamamen tek bir merkezi i\u015flem biriminin rastgele eri\u015fimli belle\u011fi i\u00e7inde i\u015flev g\u00f6r\u00fcyordu ve bu da onlar\u0131 2010&#8217;lar boyunca kurumsal verilerin \u00fcstel b\u00fcy\u00fcmesine uygun hale getirmiyordu. Veri setleri gigabaytlardan petabaytlara geni\u015fledik\u00e7e, tek cihazl\u0131 hesaplamalar pratik olmaktan \u00e7\u0131kt\u0131 ve geli\u015ftiricileri analitik hassasiyetten \u00f6d\u00fcn veren yakla\u015f\u0131mc\u0131 alt \u00f6rnekleme y\u00f6ntemlerine g\u00fcvenmeye zorlad\u0131.<\/p>\n<p>GPU h\u0131zland\u0131rmal\u0131 tek d\u00fc\u011f\u00fcml\u00fc \u00e7er\u00e7evelerin sunulmas\u0131 ge\u00e7ici bir rahatlama sa\u011flad\u0131, ancak donan\u0131m bellek tavanlar\u0131 \u00e7\u00f6z\u00fclemez bir bariyer olarak kald\u0131. Ekipler, devasa derlemeler i\u00e7in yo\u011fun kom\u015fu grafikleri i\u015flerken rutin olarak bellek a\u015f\u0131m\u0131 hatalar\u0131yla kar\u015f\u0131la\u015ft\u0131. A\u011fustos 2026 itibar\u0131yla, y\u00fcksek h\u0131zl\u0131 ara ba\u011flant\u0131lar\u0131n ve geli\u015fmi\u015f da\u011f\u0131t\u0131k grafik b\u00f6lme algoritmalar\u0131n\u0131n yak\u0131nsamas\u0131 nihayet ger\u00e7ek \u00e7oklu GPU \u00f6l\u00e7eklendirmesini m\u00fcmk\u00fcn k\u0131ld\u0131 ve tek cihazl\u0131 s\u0131n\u0131rlamalardan kesin bir uzakla\u015fmaya i\u015faret etti.<\/p>\n<h2><span class=\"ez-toc-section\" id=\"Pazar_Etkisi_ve_Kurumsal_Uygulamalar\"><\/span>Pazar Etkisi ve Kurumsal Uygulamalar<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>Biyoinformatik ve b\u00fcy\u00fck \u00f6l\u00e7ekli do\u011fal dil i\u015fleme gibi a\u015f\u0131r\u0131 veri hacimleriyle u\u011fra\u015fan end\u00fcstriler, h\u0131zl\u0131 \u00f6zellik \u00e7\u0131kar\u0131m\u0131na b\u00fcy\u00fck \u00f6l\u00e7\u00fcde g\u00fcvenir. \u0130la\u00e7 ara\u015ft\u0131rmac\u0131lar\u0131, nadir hastal\u0131k belirte\u00e7lerini belirlemek i\u00e7in milyonlarca h\u00fccresel profili ayn\u0131 anda analiz eder. Finansal kurumlar, anomali kal\u0131plar\u0131n\u0131 ger\u00e7ek zamanl\u0131 olarak tespit etmek i\u00e7in s\u00fcrekli i\u015flem de\u011fi\u015fkenleri ak\u0131\u015f\u0131n\u0131 i\u015fler. Daha h\u0131zl\u0131 y\u00fcr\u00fctme d\u00f6ng\u00fcleri, ara\u015ft\u0131rmac\u0131lar\u0131n hipotezleri test etmelerini ve model parametrelerini yinelemeli olarak ayarlamalar\u0131n\u0131 sa\u011flar.<\/p>\n<p>Donan\u0131m bekleme s\u00fcrelerinin ortadan kald\u0131r\u0131lmas\u0131, k\u00fcresel kurumsal ortamlarda veri bilimi \u00fcretkenli\u011fini d\u00f6n\u00fc\u015ft\u00fcr\u00fcr. Analistlerin toplu i\u015fleme i\u015flerinin tamamlanmas\u0131 i\u00e7in art\u0131k gece boyunca beklemesine gerek yoktur. Karma\u015f\u0131k \u00f6zellik uzaylar\u0131 i\u00e7eren petabayt \u00f6l\u00e7e\u011findeki havuzlarla \u00e7al\u0131\u015f\u0131rken bile interaktif veri ke\u015ffi uygulanabilir hale gelir. Bu yetenek, kaynak yo\u011fun AI hatlar\u0131n\u0131 i\u015fleten ekipler i\u00e7in geli\u015fmi\u015f g\u00f6rsel analiti\u011fi demokratikle\u015ftirir ve ila\u00e7 ile finans sekt\u00f6rlerindeki rekabet dinamiklerini de\u011fi\u015ftirir.<\/p>\n<h2><span class=\"ez-toc-section\" id=\"Teknik_Uygulama_Gerceklikleri\"><\/span>Teknik Uygulama Ger\u00e7eklikleri<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>Da\u011f\u0131t\u0131k grafik algoritmalar\u0131n\u0131 da\u011f\u0131tmak, y\u00fcksek h\u0131zl\u0131 ara ba\u011flant\u0131lar \u00fczerinden GPU&#8217;dan GPU&#8217;ya ileti\u015fimi koordine edebilen \u00f6zel yaz\u0131l\u0131m k\u00fct\u00fcphaneleri gerektirir. Geli\u015ftiriciler, en yak\u0131n kom\u015fu arama a\u015famas\u0131nda donan\u0131m darbo\u011fazlar\u0131ndan ka\u00e7\u0131nmak i\u00e7in bellek ay\u0131rma havuzlar\u0131n\u0131 dikkatlice yap\u0131land\u0131rmal\u0131d\u0131r. Optimize edilmi\u015f CUDA \u00e7ekirdekleri, standart Python sarmalay\u0131c\u0131lar\u0131n\u0131n alt\u0131ndaki a\u011f\u0131r i\u015fleri y\u00f6neterek mevcut veri bilimi y\u0131\u011f\u0131nlar\u0131yla sorunsuz entegrasyon sa\u011flar. Kurulu\u015flar, yeterli PCIe bant geni\u015fli\u011fi ve g\u00fc\u00e7 iletimi sa\u011flamak i\u00e7in temel sunucu altyap\u0131lar\u0131n\u0131 de\u011ferlendirmelidir.<\/p>\n<p>Donan\u0131m yat\u0131r\u0131mlar\u0131, kurumsal mimariler i\u00e7indeki gelen veri ak\u0131\u015flar\u0131n\u0131n hacmiyle orant\u0131l\u0131 olarak \u00f6l\u00e7eklenir. Modern h\u0131zland\u0131r\u0131lm\u0131\u015f bili\u015fim k\u00fcmelerini kullanan \u015firketler, eski veri al\u0131m hatlar\u0131n\u0131 yeniden yazmadan an\u0131nda verimlilik kazan\u0131mlar\u0131 elde eder. Yaz\u0131l\u0131m katman\u0131, karma\u015f\u0131k da\u011f\u0131t\u0131k sistemler mant\u0131\u011f\u0131n\u0131 soyutlayarak uygulay\u0131c\u0131lar\u0131n altyap\u0131 y\u00f6netimi yerine tamamen analitik sonu\u00e7lara odaklanmas\u0131n\u0131 sa\u011flar.<\/p>\n<h2><span class=\"ez-toc-section\" id=\"Paydas_Analizi_ve_Gelecek_Etkileri\"><\/span>Payda\u015f Analizi ve Gelecek Etkileri<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>\u00c7oklu GPU UMAP h\u0131zland\u0131rmas\u0131n\u0131n da\u011f\u0131t\u0131m\u0131, \u00e7e\u015fitli teknoloji payda\u015flar\u0131n\u0131n sorumluluklar\u0131n\u0131 ve yeteneklerini yeniden \u015fekillendirir. Kurumsal veri bilimi ekipleri, gece toplu i\u015flerini beklemek yerine modeller \u00fczerinde ger\u00e7ek zamanl\u0131 olarak yineleme yetene\u011fi kazanarak do\u011frudan en \u00e7ok fayday\u0131 sa\u011flar. Buna kar\u015f\u0131l\u0131k, eski bili\u015fim altyap\u0131lar\u0131n\u0131 y\u00fckseltmekte yava\u015f kalan kurulu\u015flar, daha h\u0131zl\u0131 biyolojik ke\u015fifler ve doland\u0131r\u0131c\u0131l\u0131k tespiti i\u00e7in bu h\u0131zland\u0131r\u0131lm\u0131\u015f hatlardan yararlanan rakiplerinin gerisinde kalma riskiyle kar\u015f\u0131 kar\u015f\u0131yad\u0131r.<\/p>\n<p>\u00d6n\u00fcm\u00fczdeki 6 ila 12 aya bak\u0131ld\u0131\u011f\u0131nda, h\u0131zland\u0131r\u0131lm\u0131\u015f boyutsall\u0131k indirgeme ara\u00e7lar\u0131n\u0131n benimsenmesi bulut ve \u015firket i\u00e7i yapay zeka laboratuvarlar\u0131nda artacakt\u0131r. Yaz\u0131l\u0131m sat\u0131c\u0131lar\u0131 muhtemelen bu \u00e7oklu GPU rutinlerini do\u011frudan ana ak\u0131m veri bilimi \u00e7er\u00e7evelerine ve g\u00f6rselle\u015ftirme panolar\u0131na entegre edecektir. Donan\u0131m \u00fcreticileri, i\u015flem s\u0131n\u0131rlar\u0131n\u0131 daha da ileri itmek i\u00e7in ara ba\u011flant\u0131 h\u0131zlar\u0131n\u0131 iyile\u015ftirmeye devam edecektir. M\u00fchendisler, kurumsal makine \u00f6\u011freniminde standart bir uygulama olarak karma\u015f\u0131k veri setlerinin neredeyse an\u0131nda g\u00f6rselle\u015ftirilmesini bekleyebilirler.<\/p>\n<p><em>Kaynak: <a href=\"https:\/\/developer.nvidia.com\/blog\/run-massive-scale-umap-in-minutes-using-multiple-gpus-without-losing-accuracy\/\" target=\"_blank\" rel=\"noopener noreferrer\">Orijinal Makale<\/a><\/em><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Nvidia, devasa y\u00fcksek boyutlu veri setlerini do\u011fruluk kayb\u0131 olmadan dakikalar i\u00e7inde i\u015flemek i\u00e7in \u00e7oklu GPU UMAP h\u0131zland\u0131rma y\u00f6ntemini duyurdu.<\/p>\n","protected":false},"author":1,"featured_media":800,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"googlesitekit_rrm_CAowrrDMDA:productID":"","footnotes":"","rank_math_focus_keyword":"Nvidia, \u00e7oklu GPU, veri g\u00f6rselle\u015ftirme, donan\u0131m, k\u00fcmeler, analitik","rank_math_title":"Nvidia, \u00c7oklu GPU Destekli UMAP ile B\u00fcy\u00fck Verileri H\u0131zland\u0131r\u0131yor","rank_math_description":"Nvidia, devasa y\u00fcksek boyutlu veri setlerini do\u011fruluk kayb\u0131 olmadan dakikalar i\u00e7inde i\u015flemek i\u00e7in \u00e7oklu GPU UMAP h\u0131zland\u0131rma y\u00f6ntemini duyurdu."},"categories":[2],"tags":[],"class_list":["post-801","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-technology"],"_links":{"self":[{"href":"https:\/\/www.tayfnews.tech\/tr\/wp-json\/wp\/v2\/posts\/801","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.tayfnews.tech\/tr\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.tayfnews.tech\/tr\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.tayfnews.tech\/tr\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.tayfnews.tech\/tr\/wp-json\/wp\/v2\/comments?post=801"}],"version-history":[{"count":0,"href":"https:\/\/www.tayfnews.tech\/tr\/wp-json\/wp\/v2\/posts\/801\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.tayfnews.tech\/tr\/wp-json\/wp\/v2\/media\/800"}],"wp:attachment":[{"href":"https:\/\/www.tayfnews.tech\/tr\/wp-json\/wp\/v2\/media?parent=801"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.tayfnews.tech\/tr\/wp-json\/wp\/v2\/categories?post=801"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.tayfnews.tech\/tr\/wp-json\/wp\/v2\/tags?post=801"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}