{"id":1577,"date":"2025-10-31T16:24:43","date_gmt":"2025-10-31T13:24:43","guid":{"rendered":"https:\/\/www.markatescilsorgulama.net\/blog\/?p=1577"},"modified":"2025-10-31T16:24:43","modified_gmt":"2025-10-31T13:24:43","slug":"makine-ogrenimi","status":"publish","type":"post","link":"https:\/\/www.markatescilsorgulama.net\/blog\/makine-ogrenimi\/","title":{"rendered":"Makine \u00d6\u011frenimi (Machine Learning) Nedir?"},"content":{"rendered":"<p>Makine \u00f6\u011frenimi terimi, bilgisayar sistemlerinin <strong data-start=\"199\" data-end=\"232\">veri arac\u0131l\u0131\u011f\u0131yla \u00f6\u011frenebilme<\/strong>, yani a\u00e7\u0131k\u00e7a programlanmadan kendilerini geli\u015ftirebilme yetene\u011fini tan\u0131mlar. Daha a\u00e7\u0131k bir ifadeyle: sistemlere \u201cbelirli bir i\u015fi nas\u0131l yapaca\u011f\u0131n\u0131\u201d sat\u0131r sat\u0131r \u00f6\u011fretilmek yerine, veriler \u00fczerinden modelin desenleri yakalay\u0131p sonu\u00e7 \u00fcretmesi sa\u011flan\u0131r. \u00d6rne\u011fin, bir sistem \u00e7ok say\u0131da ge\u00e7mi\u015f veri al\u0131r ve bu verilerden yola \u00e7\u0131karak gelecekte benzer bir durumda ne yap\u0131lmas\u0131 gerekti\u011fini tahmin eder.<\/p>\n<p><img loading=\"lazy\" decoding=\"async\" class=\"aligncenter wp-image-1578\" src=\"https:\/\/www.markatescilsorgulama.net\/blog\/wp-content\/uploads\/2025\/10\/Makine-Ogrenimi-Machine-Learning-Nedir-300x178.jpg\" alt=\"Makine \u00d6\u011frenimi (Machine Learning) Nedir\" width=\"600\" height=\"355\" srcset=\"https:\/\/www.markatescilsorgulama.net\/blog\/wp-content\/uploads\/2025\/10\/Makine-Ogrenimi-Machine-Learning-Nedir-300x178.jpg 300w, https:\/\/www.markatescilsorgulama.net\/blog\/wp-content\/uploads\/2025\/10\/Makine-Ogrenimi-Machine-Learning-Nedir-1024x606.jpg 1024w, https:\/\/www.markatescilsorgulama.net\/blog\/wp-content\/uploads\/2025\/10\/Makine-Ogrenimi-Machine-Learning-Nedir-768x455.jpg 768w, https:\/\/www.markatescilsorgulama.net\/blog\/wp-content\/uploads\/2025\/10\/Makine-Ogrenimi-Machine-Learning-Nedir-1536x909.jpg 1536w, https:\/\/www.markatescilsorgulama.net\/blog\/wp-content\/uploads\/2025\/10\/Makine-Ogrenimi-Machine-Learning-Nedir-2048x1213.jpg 2048w, https:\/\/www.markatescilsorgulama.net\/blog\/wp-content\/uploads\/2025\/10\/Makine-Ogrenimi-Machine-Learning-Nedir-990x586.jpg 990w, https:\/\/www.markatescilsorgulama.net\/blog\/wp-content\/uploads\/2025\/10\/Makine-Ogrenimi-Machine-Learning-Nedir-1320x782.jpg 1320w\" sizes=\"auto, (max-width: 600px) 100vw, 600px\" \/><\/p>\n<p>Bu tan\u0131m \u00e7er\u00e7evesinde, makine \u00f6\u011frenimi genellikle \u015f\u00f6yle tarif edilir:<\/p>\n<ul>\n<li data-start=\"781\" data-end=\"970\">Bilgisayar program\u0131, bir g\u00f6rev <strong data-start=\"812\" data-end=\"817\">T<\/strong> i\u00e7in deneyim <strong data-start=\"831\" data-end=\"836\">E<\/strong> kazand\u0131k\u00e7a ve performans \u00f6l\u00e7\u00fcs\u00fc <strong data-start=\"869\" data-end=\"874\">P<\/strong> ile de\u011ferlendirildik\u00e7e, bu g\u00f6revde daha iyi hale gelir.<\/li>\n<li data-start=\"781\" data-end=\"970\">Yani verilerden \u00f6\u011frenme ve yeni durumlara genel uzaydan (generalise) tepki verebilme s\u00f6z konusudur.<\/li>\n<\/ul>\n<p>Dolay\u0131s\u0131yla makine \u00f6\u011frenimi; yaln\u0131zca istatistik ya da klasik programlama de\u011fil, verideki desenleri \u00e7\u0131karan algoritmalar\u0131 da i\u00e7erir \u2013 bu nedenle hem m\u00fchendislik hem de veri bilimi alanlar\u0131n\u0131n kesi\u015fiminde yer al\u0131r.<\/p>\n<div id=\"ez-toc-container\" class=\"ez-toc-v2_0_78 counter-hierarchy ez-toc-counter ez-toc-grey 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=\"Toggle Table of Content\"><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.markatescilsorgulama.net\/blog\/makine-ogrenimi\/#Makine_Ogrenimi_Turleri_Nelerdir\" >Makine \u00d6\u011frenimi T\u00fcrleri Nelerdir?<\/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:\/\/www.markatescilsorgulama.net\/blog\/makine-ogrenimi\/#1_Denetimli_Ogrenme_Supervised_Learning\" >1. Denetimli \u00d6\u011frenme (Supervised Learning)<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-3\" href=\"https:\/\/www.markatescilsorgulama.net\/blog\/makine-ogrenimi\/#2_Denetimsiz_Ogrenme_Unsupervised_Learning\" >2. Denetimsiz \u00d6\u011frenme (Unsupervised Learning)<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-4\" href=\"https:\/\/www.markatescilsorgulama.net\/blog\/makine-ogrenimi\/#3_Pekistirmeli_Ogrenme_Reinforcement_Learning\" >3. Peki\u015ftirmeli \u00d6\u011frenme (Reinforcement Learning)<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-5\" href=\"https:\/\/www.markatescilsorgulama.net\/blog\/makine-ogrenimi\/#4_Yari-Denetimli_Ogrenme_Semi-Supervised_Learning\" >4. Yar\u0131-Denetimli \u00d6\u011frenme (Semi-Supervised Learning)<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-6\" href=\"https:\/\/www.markatescilsorgulama.net\/blog\/makine-ogrenimi\/#5_Kendi_Kendine_Ogrenme_Self-Supervised_Learning\" >5. Kendi Kendine \u00d6\u011frenme (Self-Supervised Learning)<\/a><\/li><\/ul><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-7\" href=\"https:\/\/www.markatescilsorgulama.net\/blog\/makine-ogrenimi\/#Makine_Ogrenimi_Nasil_Calisir\" >Makine \u00d6\u011frenimi Nas\u0131l \u00c7al\u0131\u015f\u0131r?<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-8\" href=\"https:\/\/www.markatescilsorgulama.net\/blog\/makine-ogrenimi\/#Makine_Ogrenimi_Algoritmalari\" >Makine \u00d6\u011frenimi Algoritmalar\u0131<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-9\" href=\"https:\/\/www.markatescilsorgulama.net\/blog\/makine-ogrenimi\/#Makine_Ogrenmesi_ile_Yapay_Zeka_Arasindaki_Farklar_Nelerdir\" >Makine \u00d6\u011frenmesi ile Yapay Zeka Aras\u0131ndaki Farklar Nelerdir?<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-10\" href=\"https:\/\/www.markatescilsorgulama.net\/blog\/makine-ogrenimi\/#Makine_Ogreniminin_Gunluk_Hayattaki_Kullanim_Alanlari\" >Makine \u00d6\u011freniminin G\u00fcnl\u00fck Hayattaki Kullan\u0131m Alanlar\u0131<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-11\" href=\"https:\/\/www.markatescilsorgulama.net\/blog\/makine-ogrenimi\/#Makine_Ogreniminin_Avantajlari\" >Makine \u00d6\u011freniminin Avantajlar\u0131<\/a><ul class='ez-toc-list-level-3' ><li class='ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-12\" href=\"https:\/\/www.markatescilsorgulama.net\/blog\/makine-ogrenimi\/#Kaynakca_Referanslar\" >Kaynak\u00e7a \/ Referanslar<\/a><\/li><\/ul><\/li><\/ul><\/nav><\/div>\n<h2><span class=\"ez-toc-section\" id=\"Makine_Ogrenimi_Turleri_Nelerdir\"><\/span>Makine \u00d6\u011frenimi T\u00fcrleri Nelerdir?<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p data-start=\"1457\" data-end=\"1594\">Makine \u00f6\u011frenimi algoritmalar\u0131 farkl\u0131 \u00f6\u011frenme stratejilerine g\u00f6re s\u0131n\u0131fland\u0131r\u0131l\u0131r. A\u015fa\u011f\u0131da ba\u015fl\u0131ca t\u00fcrleri ve a\u00e7\u0131klamalar\u0131 yer almaktad\u0131r:<\/p>\n<h3 data-start=\"1596\" data-end=\"1644\"><span class=\"ez-toc-section\" id=\"1_Denetimli_Ogrenme_Supervised_Learning\"><\/span>1. Denetimli \u00d6\u011frenme (Supervised Learning)<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p data-start=\"1645\" data-end=\"1961\">Bu y\u00f6ntemde algoritmaya giri\u015f verisi (input) yan\u0131nda do\u011fru \u00e7\u0131k\u0131\u015flar (label) da sunulur. Ama\u00e7: yeni girdiler kar\u015f\u0131s\u0131nda do\u011fru \u00e7\u0131kt\u0131y\u0131 tahmin edebilmek.\u00a0 \u00a0\u00d6rnek: Bir e-posta&#8217;n\u0131n spam olup olmad\u0131\u011f\u0131n\u0131 etiketleyerek g\u00f6sterip ard\u0131ndan yeni e-postalara spam m\u0131? diye karar vermesi.<\/p>\n<h3 data-start=\"1963\" data-end=\"2014\"><span class=\"ez-toc-section\" id=\"2_Denetimsiz_Ogrenme_Unsupervised_Learning\"><\/span>2. Denetimsiz \u00d6\u011frenme (Unsupervised Learning)<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p data-start=\"2015\" data-end=\"2244\">Bu y\u00f6ntemde etiketli veri yoktur; algoritma verideki desenleri, gruplamalar\u0131, gizli yap\u0131lar\u0131 ke\u015ffetmeye \u00e7al\u0131\u015f\u0131r. \u00d6rnek: M\u00fc\u015fteri verilerini grupland\u0131rarak farkl\u0131 m\u00fc\u015fteri profilleri \u00e7\u0131karmak.<\/p>\n<h3 data-start=\"2015\" data-end=\"2244\"><span class=\"ez-toc-section\" id=\"3_Pekistirmeli_Ogrenme_Reinforcement_Learning\"><\/span>3. Peki\u015ftirmeli \u00d6\u011frenme (Reinforcement Learning)<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p>Algoritma bir ortamda hareket eder, ald\u0131\u011f\u0131 aksiyonlar\u0131n sonucunda \u00f6d\u00fcl veya ceza al\u0131r ve bu \u015fekilde \u00f6\u011frenir. Ama\u00e7 \u00f6d\u00fcl\u00fc maksimize etmektir. \u00d6rnek: Otonom ara\u00e7lar\u0131n trafikte g\u00fcvenli \u015fekilde s\u00fcrmeyi \u00f6\u011frenmesi.<\/p>\n<h3 data-start=\"2550\" data-end=\"2608\"><span class=\"ez-toc-section\" id=\"4_Yari-Denetimli_Ogrenme_Semi-Supervised_Learning\"><\/span>4. Yar\u0131-Denetimli \u00d6\u011frenme (Semi-Supervised Learning)<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p data-start=\"2609\" data-end=\"2814\">Bir k\u0131sm\u0131 etiketli, b\u00fcy\u00fck k\u0131sm\u0131 etiketsiz veri i\u00e7eren durumlarda kullan\u0131l\u0131r. Etiketli verinin az oldu\u011fu ama etiketsiz verinin bol oldu\u011fu senaryolarda fayda sa\u011flar.<\/p>\n<h3 data-start=\"2816\" data-end=\"2873\"><span class=\"ez-toc-section\" id=\"5_Kendi_Kendine_Ogrenme_Self-Supervised_Learning\"><\/span>5. Kendi Kendine \u00d6\u011frenme (Self-Supervised Learning)<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p data-start=\"2874\" data-end=\"3077\">Etiket olmadan, verinin kendi i\u00e7inden g\u00f6revlendirme (pre-text task) \u00e7\u0131kararak \u00f6\u011frenme bi\u00e7imidir. \u00d6zellikle dil modelleme ve b\u00fcy\u00fck veri k\u00fcmelerinde tercih edilir.\u00a0 Bu t\u00fcrlerin her biri farkl\u0131 ama\u00e7lara hizmet eder ve ger\u00e7ek uygulamalarda birden fazla strateji birlikte kullan\u0131labilir.<\/p>\n<h2 data-start=\"2874\" data-end=\"3077\"><span class=\"ez-toc-section\" id=\"Makine_Ogrenimi_Nasil_Calisir\"><\/span>Makine \u00d6\u011frenimi Nas\u0131l \u00c7al\u0131\u015f\u0131r?<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p data-start=\"3286\" data-end=\"3362\">Makine \u00f6\u011freniminin \u00e7al\u0131\u015fma s\u00fcreci prensip olarak a\u015fa\u011f\u0131daki a\u015famalar\u0131 i\u00e7erir:<\/p>\n<ol data-start=\"3364\" data-end=\"4638\">\n<li data-start=\"3364\" data-end=\"3510\">\n<p data-start=\"3367\" data-end=\"3510\"><strong data-start=\"3367\" data-end=\"3383\">Veri Toplama<\/strong><br data-start=\"3383\" data-end=\"3386\" \/>\u0130lgili problemin \u00e7\u00f6z\u00fcm\u00fc i\u00e7in ge\u00e7mi\u015f veri seti haz\u0131rlan\u0131r. \u00d6rne\u011fin m\u00fc\u015fteri al\u0131\u015fveri\u015fleri, sens\u00f6r kay\u0131tlar\u0131, g\u00f6r\u00fcnt\u00fcler vb.<\/p>\n<\/li>\n<li data-start=\"3512\" data-end=\"3685\">\n<p data-start=\"3515\" data-end=\"3685\"><strong data-start=\"3515\" data-end=\"3554\">Veri \u00d6n \u0130\u015fleme (Data Preprocessing)<\/strong><br data-start=\"3554\" data-end=\"3557\" \/>Veriler temizlenir (eksik de\u011ferler, ayk\u0131r\u0131 de\u011ferler ele al\u0131n\u0131r), uygun formata d\u00f6n\u00fc\u015ft\u00fcr\u00fcl\u00fcr, gerekirse \u00f6l\u00e7eklendirme yap\u0131l\u0131r.<\/p>\n<\/li>\n<li data-start=\"3687\" data-end=\"3875\">\n<p data-start=\"3690\" data-end=\"3875\"><strong data-start=\"3690\" data-end=\"3736\">\u00d6zellik M\u00fchendisli\u011fi (Feature Engineering)<\/strong><br data-start=\"3736\" data-end=\"3739\" \/>Modelin \u00f6\u011frenmesi i\u00e7in \u00f6nemli olabilecek de\u011fi\u015fkenler (\u00f6zellikler) se\u00e7ilir veya t\u00fcretilir. Bu ad\u0131m model ba\u015far\u0131s\u0131 a\u00e7\u0131s\u0131ndan kritiktir.<\/p>\n<\/li>\n<li data-start=\"3877\" data-end=\"4065\">\n<p data-start=\"3880\" data-end=\"4065\"><strong data-start=\"3880\" data-end=\"3917\">Model Se\u00e7imi ve E\u011fitim (Training)<\/strong><br data-start=\"3917\" data-end=\"3920\" \/>Uygun algoritma belirlenir (\u00f6rne\u011fin regresyon, karar a\u011fac\u0131, sinir a\u011f\u0131), e\u011fitim verisi \u00fczerinde bu model \u00f6\u011frenir \u2014 yani parametreler ayarlan\u0131r.<\/p>\n<\/li>\n<li data-start=\"4067\" data-end=\"4306\">\n<p data-start=\"4070\" data-end=\"4306\"><strong data-start=\"4070\" data-end=\"4100\">De\u011ferlendirme (Evaluation)<\/strong><br data-start=\"4100\" data-end=\"4103\" \/>Model test verisi \u00fczerinde \u00e7al\u0131\u015ft\u0131r\u0131larak do\u011fruluk, hata oran\u0131, genel ge\u00e7erlik gibi metriklerle de\u011ferlendirilir. A\u015f\u0131r\u0131 \u00f6\u011frenme (overfitting) veya yetersiz \u00f6\u011frenme (underfitting) durumu kontrol edilir.<\/p>\n<\/li>\n<li data-start=\"4308\" data-end=\"4482\">\n<p data-start=\"4311\" data-end=\"4482\"><strong data-start=\"4311\" data-end=\"4355\">Modelin Uygulamaya Al\u0131nmas\u0131 (Deployment)<\/strong><br data-start=\"4355\" data-end=\"4358\" \/>Model i\u015fletim ortam\u0131na al\u0131n\u0131r, ger\u00e7ek verilerle tahminler yap\u0131l\u0131r. Performans\u0131 izlenir, gerekirse yeniden e\u011fitim yap\u0131l\u0131r.<\/p>\n<\/li>\n<li data-start=\"4484\" data-end=\"4638\">\n<p data-start=\"4487\" data-end=\"4638\"><strong data-start=\"4487\" data-end=\"4510\">Bak\u0131m ve G\u00fcncelleme<\/strong><br data-start=\"4510\" data-end=\"4513\" \/>Zamanla veri yap\u0131s\u0131 de\u011fi\u015febilir, model eskiyebilir. Bu y\u00fczden modelin d\u00fczenli g\u00fcncellenmesi ve yeniden e\u011fitilmesi gerekir.<\/p>\n<\/li>\n<\/ol>\n<p data-start=\"4640\" data-end=\"4736\">Bu ad\u0131mlar bir d\u00f6ng\u00fc \u015feklinde i\u015fletilir ve makine \u00f6\u011frenimi s\u00fcre\u00e7leri s\u00fcrekli iyile\u015ftirme i\u00e7erir.<\/p>\n<h2 data-start=\"4640\" data-end=\"4736\"><span class=\"ez-toc-section\" id=\"Makine_Ogrenimi_Algoritmalari\"><\/span>Makine \u00d6\u011frenimi Algoritmalar\u0131<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p data-start=\"4823\" data-end=\"4941\">Makine \u00f6\u011frenimi algoritmalar\u0131, yukar\u0131da bahsedilen t\u00fcrlere g\u00f6re de\u011fi\u015fmekle birlikte a\u015fa\u011f\u0131daki \u00f6nemli \u00f6rnekleri i\u00e7erir:<\/p>\n<ul data-start=\"4943\" data-end=\"6323\">\n<li data-start=\"4943\" data-end=\"5072\">\n<p data-start=\"4945\" data-end=\"5072\"><strong data-start=\"4945\" data-end=\"4987\">Do\u011frusal Regresyon (Linear Regression)<\/strong>: S\u00fcrekli de\u011ferlerin tahmininde kullan\u0131l\u0131r.<\/p>\n<\/li>\n<li data-start=\"5073\" data-end=\"5216\">\n<p data-start=\"5075\" data-end=\"5216\"><strong data-start=\"5075\" data-end=\"5119\">Lojistik Regresyon (Logistic Regression)<\/strong>: \u0130kili s\u0131n\u0131fland\u0131rma problemlerinde yayg\u0131n kullan\u0131l\u0131r.<\/p>\n<\/li>\n<li data-start=\"5217\" data-end=\"5343\">\n<p data-start=\"5219\" data-end=\"5343\"><strong data-start=\"5219\" data-end=\"5250\">Karar A\u011fac\u0131 (Decision Tree)<\/strong>: Veri \u00fczerinde dallanma yaparak karar veren model.<\/p>\n<\/li>\n<li data-start=\"5344\" data-end=\"5502\">\n<p data-start=\"5346\" data-end=\"5502\">Destek Vekt\u00f6r Makinesi (SVM \u2013 Support Vector Machine): S\u0131n\u0131fland\u0131rma ve regresyonda kullan\u0131lan g\u00fc\u00e7l\u00fc bir y\u00f6ntem.<\/p>\n<\/li>\n<li data-start=\"5503\" data-end=\"5669\">\n<p data-start=\"5505\" data-end=\"5669\">Naive Bayes S\u0131n\u0131fland\u0131r\u0131c\u0131s\u0131 (Naive Bayes): Olas\u0131l\u0131ksal \u00f6\u011frenme y\u00f6ntemi; genellikle metin s\u0131n\u0131fland\u0131rmas\u0131nda kullan\u0131l\u0131r.<\/p>\n<\/li>\n<li data-start=\"5670\" data-end=\"5846\">\n<p data-start=\"5672\" data-end=\"5846\">k\u2011En Yak\u0131n Kom\u015fu (k-Nearest Neighbors, k-NN): Yeni bir veriyi, en benzer ge\u00e7mi\u015f veriler \u00fczerinden s\u0131n\u0131fland\u0131r\u0131r ya da tahmin eder.<\/p>\n<\/li>\n<li data-start=\"5847\" data-end=\"6018\">\n<p data-start=\"5849\" data-end=\"6018\">Rastgele Orman (Random Forest): Birden \u00e7ok karar a\u011fac\u0131n\u0131n ensemble (\u00e7oklu-model) yakla\u015f\u0131m\u0131yla birle\u015ftirilmesiyle olu\u015fturulur.<\/p>\n<\/li>\n<li data-start=\"6019\" data-end=\"6150\">\n<p data-start=\"6021\" data-end=\"6150\">**K\u2011means K\u00fcmeleme: Denetimsiz \u00f6\u011frenmede yayg\u0131n olan, veriyi gruplara ay\u0131ran algoritma.<\/p>\n<\/li>\n<li data-start=\"6019\" data-end=\"6150\">\n<p data-start=\"6021\" data-end=\"6150\">Ayr\u0131ca boyut indirgeme, gradyan art\u0131r\u0131m\u0131 (gradient boosting), derin \u00f6\u011frenme (deep learning) gibi daha ileri y\u00f6ntemler de vard\u0131r.<\/p>\n<\/li>\n<\/ul>\n<p data-start=\"6325\" data-end=\"6448\">Her algoritman\u0131n g\u00fc\u00e7l\u00fc ve zay\u0131f y\u00f6nleri vard\u0131r; problem tipi, veri yap\u0131s\u0131, hedef vs. g\u00f6z \u00f6n\u00fcne al\u0131narak se\u00e7im yap\u0131lmal\u0131d\u0131r.<\/p>\n<h2 data-start=\"6325\" data-end=\"6448\"><span class=\"ez-toc-section\" id=\"Makine_Ogrenmesi_ile_Yapay_Zeka_Arasindaki_Farklar_Nelerdir\"><\/span>Makine \u00d6\u011frenmesi ile Yapay Zeka Aras\u0131ndaki Farklar Nelerdir?<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p data-start=\"6566\" data-end=\"6673\">Yapay Zeka (AI) ve makine \u00f6\u011frenimi (ML) terimleri s\u0131k kar\u0131\u015ft\u0131r\u0131l\u0131r; ancak aralar\u0131nda \u00f6nemli farklar vard\u0131r:<\/p>\n<ul data-start=\"6675\" data-end=\"7399\">\n<li data-start=\"6675\" data-end=\"6849\">\n<p data-start=\"6677\" data-end=\"6849\">Yapay zeka, makinelerin insan benzeri <strong data-start=\"6715\" data-end=\"6747\">zek\u00e2, alg\u0131lama, ak\u0131l y\u00fcr\u00fctme<\/strong> gibi yetenekler sergilemesini hedefleyen geni\u015f bir aland\u0131r.<\/p>\n<\/li>\n<li data-start=\"6850\" data-end=\"7131\">\n<p data-start=\"6852\" data-end=\"7131\">Makine \u00f6\u011frenimi ise, bu geni\u015f alan\u0131n i\u00e7erisinde yer alan ve <strong data-start=\"6912\" data-end=\"6939\">veri kullanarak \u00f6\u011frenme<\/strong> mekanizmas\u0131na odaklanan \u00f6zel bir disiplindir. Ba\u015fka bir deyi\u015fle: t\u00fcm ML sistemleri AI sistemidir ama t\u00fcm AI sistemleri ML kullanmak zorunda de\u011fildir.<\/p>\n<\/li>\n<li data-start=\"7132\" data-end=\"7275\">\n<p data-start=\"7134\" data-end=\"7143\">\u00d6zetle:<\/p>\n<\/li>\n<\/ul>\n<p data-start=\"7134\" data-end=\"7143\">AI: \u201cMakineler nas\u0131l insan benzeri davran\u0131\u015f sergiler?\u201d<\/p>\n<p data-start=\"7209\" data-end=\"7275\">ML: \u201cMakinelere verilerden \u00f6\u011frenme yetene\u011fi nas\u0131l kazand\u0131r\u0131l\u0131r?\u201d<\/p>\n<ul data-start=\"6675\" data-end=\"7399\">\n<li data-start=\"7276\" data-end=\"7399\">\n<p data-start=\"7278\" data-end=\"7399\">Bu ili\u015fkiler, \u00f6zellikle derin \u00f6\u011frenme gibi alt alanlarda daha da belirginle\u015fir.<\/p>\n<\/li>\n<\/ul>\n<p data-start=\"7401\" data-end=\"7623\">Bu ayr\u0131m, i\u00e7erik \u00fcretiminde ve teknoloji de\u011ferlendirmelerinde \u00f6nemli bir perspektif sa\u011flar \u2013 \u00f6zellikle \u201cmakine \u00f6\u011frenimi algoritmalar\u0131\u201d derken asl\u0131nda \u201cveriden \u00f6\u011frenebilen modeller\u201d \u00fczerinde konu\u015ftu\u011fumuzu bilmek faydal\u0131d\u0131r.<\/p>\n<p><img loading=\"lazy\" decoding=\"async\" class=\"wp-image-1579 size-full\" src=\"https:\/\/www.markatescilsorgulama.net\/blog\/wp-content\/uploads\/2025\/10\/ai-technology-brain-background-d.jpg\" alt=\"Makine \u00d6\u011frenimi (Machine Learning) Nedir\" width=\"600\" height=\"400\" srcset=\"https:\/\/www.markatescilsorgulama.net\/blog\/wp-content\/uploads\/2025\/10\/ai-technology-brain-background-d.jpg 600w, https:\/\/www.markatescilsorgulama.net\/blog\/wp-content\/uploads\/2025\/10\/ai-technology-brain-background-d-300x200.jpg 300w, https:\/\/www.markatescilsorgulama.net\/blog\/wp-content\/uploads\/2025\/10\/ai-technology-brain-background-d-414x276.jpg 414w, https:\/\/www.markatescilsorgulama.net\/blog\/wp-content\/uploads\/2025\/10\/ai-technology-brain-background-d-470x313.jpg 470w, https:\/\/www.markatescilsorgulama.net\/blog\/wp-content\/uploads\/2025\/10\/ai-technology-brain-background-d-130x86.jpg 130w, https:\/\/www.markatescilsorgulama.net\/blog\/wp-content\/uploads\/2025\/10\/ai-technology-brain-background-d-187x124.jpg 187w\" sizes=\"auto, (max-width: 600px) 100vw, 600px\" \/><\/p>\n<h2 data-start=\"7401\" data-end=\"7623\"><span class=\"ez-toc-section\" id=\"Makine_Ogreniminin_Gunluk_Hayattaki_Kullanim_Alanlari\"><\/span>Makine \u00d6\u011freniminin G\u00fcnl\u00fck Hayattaki Kullan\u0131m Alanlar\u0131<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p data-start=\"7734\" data-end=\"7831\">Makine \u00f6\u011frenimi g\u00fcn\u00fcm\u00fczde geni\u015f bir yelpazede kullan\u0131lmaktad\u0131r. A\u015fa\u011f\u0131da baz\u0131 \u00f6rnekler yer al\u0131yor:<\/p>\n<ul data-start=\"7833\" data-end=\"8714\">\n<li data-start=\"7833\" data-end=\"7966\">\n<p data-start=\"7835\" data-end=\"7966\"><strong data-start=\"7835\" data-end=\"7855\">\u00d6neri sistemleri<\/strong>: Online al\u0131\u015fveri\u015f ya da medya platformlar\u0131 kullan\u0131c\u0131n\u0131n \u00f6nceki davran\u0131\u015flar\u0131na g\u00f6re \u00fcr\u00fcn ya da i\u00e7erik \u00f6nerir.<\/p>\n<\/li>\n<li data-start=\"7967\" data-end=\"8094\">\n<p data-start=\"7969\" data-end=\"8094\"><strong data-start=\"7969\" data-end=\"8013\">Doland\u0131r\u0131c\u0131l\u0131k tespiti (fraud detection)<\/strong>: Bankac\u0131l\u0131k ve finans sistemlerinde \u015f\u00fcpheli i\u015flemler algoritmalarla yakalan\u0131r.<\/p>\n<\/li>\n<li data-start=\"8095\" data-end=\"8201\">\n<p data-start=\"8097\" data-end=\"8201\"><strong data-start=\"8097\" data-end=\"8115\">Siber g\u00fcvenlik<\/strong>: Anomalileri tespit edebilen ve bilinmeyen sald\u0131r\u0131lara kar\u015f\u0131 \u00f6\u011frenebilen sistemler.<\/p>\n<\/li>\n<li data-start=\"8202\" data-end=\"8296\">\n<p data-start=\"8204\" data-end=\"8296\"><strong data-start=\"8204\" data-end=\"8225\">Sa\u011fl\u0131k hizmetleri<\/strong>: G\u00f6r\u00fcnt\u00fcleme verilerinden hastal\u0131k s\u0131n\u0131fland\u0131rmas\u0131, prognoz analizi.<\/p>\n<\/li>\n<li data-start=\"8297\" data-end=\"8390\">\n<p data-start=\"8299\" data-end=\"8390\"><strong data-start=\"8299\" data-end=\"8319\">Otonom sistemler<\/strong>: S\u00fcr\u00fcc\u00fcs\u00fcz ara\u00e7lar, robotik sistemler \u00e7evreyi alg\u0131lay\u0131p karar verir.<\/p>\n<\/li>\n<li data-start=\"8391\" data-end=\"8508\">\n<p data-start=\"8393\" data-end=\"8508\"><strong data-start=\"8393\" data-end=\"8429\">M\u00fc\u015fteri hizmetleri ve chatbotlar<\/strong>: Kullan\u0131c\u0131 etkile\u015fimlerine g\u00f6re metin ya da konu\u015fma temelli yan\u0131tlar \u00fcretir.<\/p>\n<\/li>\n<li data-start=\"8509\" data-end=\"8714\">\n<p data-start=\"8511\" data-end=\"8714\"><strong data-start=\"8511\" data-end=\"8555\">\u00dcretim ve bak\u0131m (predictive maintenance)<\/strong>: Sens\u00f6r verilerine dayanarak ar\u0131zalar\u0131 \u00f6nceden tahmin eder.<\/p>\n<\/li>\n<\/ul>\n<h2><span class=\"ez-toc-section\" id=\"Makine_Ogreniminin_Avantajlari\"><\/span>Makine \u00d6\u011freniminin Avantajlar\u0131<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p data-start=\"8802\" data-end=\"8872\">Makine \u00f6\u011frenimi teknolojilerinin sundu\u011fu ba\u015fl\u0131ca avantajlar \u015funlard\u0131r:<\/p>\n<ul data-start=\"8874\" data-end=\"9561\">\n<li data-start=\"8874\" data-end=\"9029\">\n<p data-start=\"8876\" data-end=\"9029\"><strong data-start=\"8876\" data-end=\"8900\">Otomatikle\u015fme ve h\u0131z<\/strong>: Manuel olarak yap\u0131lamayacak kadar b\u00fcy\u00fck veriler \u00fczerinde otomatik analiz ve \u00f6\u011frenme sa\u011flayarak karar s\u00fcre\u00e7lerini h\u0131zland\u0131r\u0131r.<\/p>\n<\/li>\n<li data-start=\"9030\" data-end=\"9197\">\n<p data-start=\"9032\" data-end=\"9197\"><strong data-start=\"9032\" data-end=\"9051\">\u00d6ng\u00f6r\u00fc yetene\u011fi<\/strong>: Ge\u00e7mi\u015f verilerden \u00f6\u011frenerek gelece\u011fe dair tahminler yapabilir; bu da risk y\u00f6netimi, pazarlama stratejisi gibi alanlarda \u00f6nemli avantaj sa\u011flar.<\/p>\n<\/li>\n<li data-start=\"9198\" data-end=\"9320\">\n<p data-start=\"9200\" data-end=\"9320\"><strong data-start=\"9200\" data-end=\"9219\">Ki\u015fiselle\u015ftirme<\/strong>: Kullan\u0131c\u0131 verilerine g\u00f6re bireysel \u00f6neriler, deneyimler sunabilir; m\u00fc\u015fteri memnuniyetini art\u0131r\u0131r.<\/p>\n<\/li>\n<li data-start=\"9321\" data-end=\"9453\">\n<p data-start=\"9323\" data-end=\"9453\"><strong data-start=\"9323\" data-end=\"9343\">Rekabet avantaj\u0131<\/strong>: Veri-yo\u011fun i\u015fletmelerde makine \u00f6\u011frenimi kullan\u0131m\u0131, daha iyi operasyonel verimlilik ve yenilik\u00e7ilik sa\u011flar.<\/p>\n<\/li>\n<li data-start=\"9454\" data-end=\"9561\">\n<p data-start=\"9456\" data-end=\"9561\"><strong data-start=\"9456\" data-end=\"9478\">Veri de\u011feri \u00fcretme<\/strong>: Sahip olunan verilerin \u201cham\u201d halden \u00e7\u0131kar\u0131larak i\u015f de\u011ferine d\u00f6n\u00fc\u015fmesini sa\u011flar.<\/p>\n<\/li>\n<\/ul>\n<h3 data-start=\"220\" data-end=\"253\"><span class=\"ez-toc-section\" id=\"Kaynakca_Referanslar\"><\/span><strong data-start=\"227\" data-end=\"253\">Kaynak\u00e7a \/ Referanslar<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h3>\n<ol data-start=\"254\" data-end=\"2270\">\n<li data-start=\"254\" data-end=\"381\">\n<p data-start=\"257\" data-end=\"381\">Google Developers \u2013 <em data-start=\"277\" data-end=\"304\">What is Machine Learning?<\/em><br data-start=\"304\" data-end=\"307\" \/><a class=\"decorated-link\" href=\"https:\/\/developers.google.com\/machine-learning\/intro-to-ml\/what-is-ml?utm_source=chatgpt.com\" target=\"_new\" rel=\"noopener\" data-start=\"310\" data-end=\"379\">https:\/\/developers.google.com\/machine-learning\/intro-to-ml\/what-is-ml<\/a><\/p>\n<\/li>\n<li data-start=\"382\" data-end=\"514\">\n<p data-start=\"385\" data-end=\"514\">SAS \u2013 <em data-start=\"391\" data-end=\"440\">Machine Learning: What it is and why it matters<\/em><br data-start=\"440\" data-end=\"443\" \/><a class=\"decorated-link\" href=\"https:\/\/www.sas.com\/en_us\/insights\/analytics\/machine-learning.html?utm_source=chatgpt.com\" target=\"_new\" rel=\"noopener\" data-start=\"446\" data-end=\"512\">https:\/\/www.sas.com\/en_us\/insights\/analytics\/machine-learning.html<\/a><\/p>\n<\/li>\n<li data-start=\"515\" data-end=\"614\">\n<p data-start=\"518\" data-end=\"614\">IBM \u2013 <em data-start=\"524\" data-end=\"551\">Types of Machine Learning<\/em><br data-start=\"551\" data-end=\"554\" \/><a class=\"decorated-link\" href=\"https:\/\/www.ibm.com\/think\/topics\/machine-learning-types?utm_source=chatgpt.com\" target=\"_new\" rel=\"noopener\" data-start=\"557\" data-end=\"612\">https:\/\/www.ibm.com\/think\/topics\/machine-learning-types<\/a><\/p>\n<\/li>\n<li data-start=\"615\" data-end=\"749\">\n<p data-start=\"618\" data-end=\"749\">TechTarget \u2013 <em data-start=\"631\" data-end=\"665\">Machine Learning (ML) Definition<\/em><br data-start=\"665\" data-end=\"668\" \/><a class=\"decorated-link\" href=\"https:\/\/www.techtarget.com\/searchenterpriseai\/definition\/machine-learning-ML?utm_source=chatgpt.com\" target=\"_new\" rel=\"noopener\" data-start=\"671\" data-end=\"747\">https:\/\/www.techtarget.com\/searchenterpriseai\/definition\/machine-learning-ML<\/a><\/p>\n<\/li>\n<li data-start=\"750\" data-end=\"857\">\n<p data-start=\"753\" data-end=\"857\">Coursera \u2013 <em data-start=\"764\" data-end=\"791\">What is Machine Learning?<\/em><br data-start=\"791\" data-end=\"794\" \/><a class=\"decorated-link\" href=\"https:\/\/www.coursera.org\/articles\/what-is-machine-learning?utm_source=chatgpt.com\" target=\"_new\" rel=\"noopener\" data-start=\"797\" data-end=\"855\">https:\/\/www.coursera.org\/articles\/what-is-machine-learning<\/a><\/p>\n<\/li>\n<li data-start=\"858\" data-end=\"945\">\n<p data-start=\"861\" data-end=\"945\">Wikipedia \u2013 <em data-start=\"873\" data-end=\"891\">Machine Learning<\/em><br data-start=\"891\" data-end=\"894\" \/><a class=\"decorated-link\" href=\"https:\/\/en.wikipedia.org\/wiki\/Machine_learning?utm_source=chatgpt.com\" target=\"_new\" rel=\"noopener\" data-start=\"897\" data-end=\"943\">https:\/\/en.wikipedia.org\/wiki\/Machine_learning<\/a><\/p>\n<\/li>\n<li data-start=\"946\" data-end=\"1049\">\n<p data-start=\"949\" data-end=\"1049\">DataCamp \u2013 <em data-start=\"960\" data-end=\"987\">What is Machine Learning?<\/em><br data-start=\"987\" data-end=\"990\" \/><a class=\"decorated-link\" href=\"https:\/\/www.datacamp.com\/blog\/what-is-machine-learning?utm_source=chatgpt.com\" target=\"_new\" rel=\"noopener\" data-start=\"993\" data-end=\"1047\">https:\/\/www.datacamp.com\/blog\/what-is-machine-learning<\/a><\/p>\n<\/li>\n<li data-start=\"1050\" data-end=\"1223\">\n<p data-start=\"1053\" data-end=\"1223\">Simplilearn \u2013 <em data-start=\"1067\" data-end=\"1126\">10 Algorithms Every Machine Learning Engineer Should Know<\/em><br data-start=\"1126\" data-end=\"1129\" \/><a class=\"decorated-link\" href=\"https:\/\/www.simplilearn.com\/10-algorithms-machine-learning-engineers-need-to-know-article?utm_source=chatgpt.com\" target=\"_new\" rel=\"noopener\" data-start=\"1132\" data-end=\"1221\">https:\/\/www.simplilearn.com\/10-algorithms-machine-learning-engineers-need-to-know-article<\/a><\/p>\n<\/li>\n<li data-start=\"1224\" data-end=\"1373\">\n<p data-start=\"1227\" data-end=\"1373\">GeeksforGeeks \u2013 <em data-start=\"1243\" data-end=\"1281\">Types of Machine Learning Algorithms<\/em><br data-start=\"1281\" data-end=\"1284\" \/><a class=\"decorated-link\" href=\"https:\/\/www.geeksforgeeks.org\/machine-learning\/types-of-machine-learning-algorithms\/?utm_source=chatgpt.com\" target=\"_new\" rel=\"noopener\" data-start=\"1287\" data-end=\"1371\">https:\/\/www.geeksforgeeks.org\/machine-learning\/types-of-machine-learning-algorithms\/<\/a><\/p>\n<\/li>\n<li data-start=\"1374\" data-end=\"1526\">\n<p data-start=\"1378\" data-end=\"1526\">Machine Learning Mastery \u2013 <em data-start=\"1405\" data-end=\"1444\">A Tour of Machine Learning Algorithms<\/em><br data-start=\"1444\" data-end=\"1447\" \/><a class=\"decorated-link\" href=\"https:\/\/machinelearningmastery.com\/a-tour-of-machine-learning-algorithms\/\" target=\"_new\" rel=\"noopener\" data-start=\"1451\" data-end=\"1524\">https:\/\/machinelearningmastery.com\/a-tour-of-machine-learning-algorithms\/<\/a><\/p>\n<\/li>\n<li data-start=\"1527\" data-end=\"1675\">\n<p data-start=\"1531\" data-end=\"1675\">Cloud Google \u2013 <em data-start=\"1546\" data-end=\"1592\">Artificial Intelligence vs. Machine Learning<\/em><br data-start=\"1592\" data-end=\"1595\" \/><a class=\"decorated-link\" href=\"https:\/\/cloud.google.com\/learn\/artificial-intelligence-vs-machine-learning?utm_source=chatgpt.com\" target=\"_new\" rel=\"noopener\" data-start=\"1599\" data-end=\"1673\">https:\/\/cloud.google.com\/learn\/artificial-intelligence-vs-machine-learning<\/a><\/p>\n<\/li>\n<li data-start=\"1676\" data-end=\"1865\">\n<p data-start=\"1680\" data-end=\"1865\">TechTarget \u2013 <em data-start=\"1693\" data-end=\"1751\">AI vs Machine Learning vs Deep Learning: Key Differences<\/em><br data-start=\"1751\" data-end=\"1754\" \/><a class=\"decorated-link\" href=\"https:\/\/www.techtarget.com\/searchenterpriseai\/tip\/AI-vs-machine-learning-vs-deep-learning-Key-differences?utm_source=chatgpt.com\" target=\"_new\" rel=\"noopener\" data-start=\"1758\" data-end=\"1863\">https:\/\/www.techtarget.com\/searchenterpriseai\/tip\/AI-vs-machine-learning-vs-deep-learning-Key-differences<\/a><\/p>\n<\/li>\n<li data-start=\"1866\" data-end=\"2011\">\n<p data-start=\"1870\" data-end=\"2011\">Analytics Vidhya \u2013 <em data-start=\"1889\" data-end=\"1926\">Machine Learning Workflow Explained<\/em><br data-start=\"1926\" data-end=\"1929\" \/><a class=\"decorated-link cursor-pointer\" target=\"_new\" rel=\"noopener\" data-start=\"1933\" data-end=\"2009\">https:\/\/www.analyticsvidhya.com\/blog\/2020\/10\/how-does-machine-learning-work\/\u00a0<\/a><\/p>\n<\/li>\n<li data-start=\"2012\" data-end=\"2117\">\n<p data-start=\"2016\" data-end=\"2117\">Big Data Turkey \u2013 <em data-start=\"2034\" data-end=\"2059\">Makine \u00d6\u011frenmesi Nedir?<\/em><br data-start=\"2059\" data-end=\"2062\" \/><a class=\"decorated-link cursor-pointer\" target=\"_new\" rel=\"noopener\" data-start=\"2066\" data-end=\"2115\">https:\/\/bigdataturkey.com\/makine-ogrenmesi-nedir\/<\/a><\/p>\n<\/li>\n<li data-start=\"2118\" data-end=\"2270\">\n<p data-start=\"2122\" data-end=\"2270\">Global AI Hub T\u00fcrkiye \u2013 <em data-start=\"2146\" data-end=\"2187\">Makine \u00d6\u011frenmesi ve Yapay Zeka \u0130li\u015fkisi<\/em><br data-start=\"2187\" data-end=\"2190\" \/><a class=\"decorated-link cursor-pointer\" target=\"_new\" rel=\"noopener\" data-start=\"2194\" data-end=\"2268\">https:\/\/globalaihub.com\/machine-learning-ve-yapay-zeka-arasindaki-farklar\/<\/a><\/p>\n<\/li>\n<\/ol>\n","protected":false},"excerpt":{"rendered":"<p>Makine \u00f6\u011frenimi terimi, bilgisayar sistemlerinin veri arac\u0131l\u0131\u011f\u0131yla \u00f6\u011frenebilme, yani a\u00e7\u0131k\u00e7a programlanmadan kendilerini geli\u015ftirebilme yetene\u011fini tan\u0131mlar. Daha a\u00e7\u0131k bir ifadeyle: sistemlere \u201cbelirli bir i\u015fi nas\u0131l yapaca\u011f\u0131n\u0131\u201d sat\u0131r sat\u0131r \u00f6\u011fretilmek yerine, veriler \u00fczerinden modelin desenleri yakalay\u0131p sonu\u00e7 \u00fcretmesi sa\u011flan\u0131r. \u00d6rne\u011fin, bir sistem \u00e7ok say\u0131da ge\u00e7mi\u015f veri al\u0131r ve bu verilerden yola \u00e7\u0131karak gelecekte benzer bir durumda ne [&hellip;]<\/p>\n","protected":false},"author":3,"featured_media":1578,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[1],"tags":[],"class_list":["post-1577","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-web-site"],"views":356,"_links":{"self":[{"href":"https:\/\/www.markatescilsorgulama.net\/blog\/wp-json\/wp\/v2\/posts\/1577","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.markatescilsorgulama.net\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.markatescilsorgulama.net\/blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.markatescilsorgulama.net\/blog\/wp-json\/wp\/v2\/users\/3"}],"replies":[{"embeddable":true,"href":"https:\/\/www.markatescilsorgulama.net\/blog\/wp-json\/wp\/v2\/comments?post=1577"}],"version-history":[{"count":1,"href":"https:\/\/www.markatescilsorgulama.net\/blog\/wp-json\/wp\/v2\/posts\/1577\/revisions"}],"predecessor-version":[{"id":1580,"href":"https:\/\/www.markatescilsorgulama.net\/blog\/wp-json\/wp\/v2\/posts\/1577\/revisions\/1580"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.markatescilsorgulama.net\/blog\/wp-json\/wp\/v2\/media\/1578"}],"wp:attachment":[{"href":"https:\/\/www.markatescilsorgulama.net\/blog\/wp-json\/wp\/v2\/media?parent=1577"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.markatescilsorgulama.net\/blog\/wp-json\/wp\/v2\/categories?post=1577"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.markatescilsorgulama.net\/blog\/wp-json\/wp\/v2\/tags?post=1577"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}