{"id":1908,"date":"2026-07-06T09:57:42","date_gmt":"2026-07-06T06:57:42","guid":{"rendered":"https:\/\/www.markatescilsorgulama.net\/blog\/?p=1908"},"modified":"2026-07-06T09:57:42","modified_gmt":"2026-07-06T06:57:42","slug":"machine-learning-nedir","status":"publish","type":"post","link":"https:\/\/www.markatescilsorgulama.net\/blog\/machine-learning-nedir\/","title":{"rendered":"Machine Learning Nedir? Yapay Zekadan Fark\u0131 Nedir"},"content":{"rendered":"<p><span style=\"font-weight: 400;\">Yapay zeka son y\u0131llar\u0131n en \u00e7ok konu\u015fulan teknolojilerinden biri haline geldi. Chatbot\u2019lardan \u00f6neri sistemlerine, g\u00f6r\u00fcnt\u00fc tan\u0131madan sesli asistanlara kadar pek \u00e7ok dijital deneyimin arkas\u0131nda yapay zeka teknolojileri yer al\u0131yor. Ancak bu alanda s\u0131k\u00e7a kar\u0131\u015ft\u0131r\u0131lan iki kavram var: <\/span><b>yapay zeka<\/b><span style=\"font-weight: 400;\"> ve <\/span><b>machine learning<\/b><span style=\"font-weight: 400;\">, yani <\/span><b>makine \u00f6\u011frenmesi<\/b><span style=\"font-weight: 400;\">.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Peki machine learning nedir? Yapay zekadan fark\u0131 nedir? Her yapay zeka sistemi machine learning kullan\u0131r m\u0131? Machine learning g\u00fcnl\u00fck hayatta nerelerde kar\u015f\u0131m\u0131za \u00e7\u0131kar? Bu yaz\u0131da machine learning kavram\u0131n\u0131, <a href=\"https:\/\/gemini.google.com\/app?hl=tr\" target=\"_blank\" rel=\"noopener\">yapay zeka<\/a> ile ili\u015fkisini, \u00e7al\u0131\u015fma mant\u0131\u011f\u0131n\u0131, kullan\u0131m alanlar\u0131n\u0131 ve i\u015fletmeler i\u00e7in neden \u00f6nemli oldu\u011funu detayl\u0131 \u015fekilde ele al\u0131yoruz.<\/span><\/p>\n<p style=\"text-align: center;\"><span style=\"font-weight: 400;\"><img loading=\"lazy\" decoding=\"async\" class=\"alignnone  wp-image-1909\" src=\"https:\/\/www.markatescilsorgulama.net\/blog\/wp-content\/uploads\/2026\/07\/Machine-Learning-Nedir-Yapay-Zekadan-Farki-Nedir1-300x163.jpg\" alt=\"\" width=\"592\" height=\"322\" srcset=\"https:\/\/www.markatescilsorgulama.net\/blog\/wp-content\/uploads\/2026\/07\/Machine-Learning-Nedir-Yapay-Zekadan-Farki-Nedir1-300x163.jpg 300w, https:\/\/www.markatescilsorgulama.net\/blog\/wp-content\/uploads\/2026\/07\/Machine-Learning-Nedir-Yapay-Zekadan-Farki-Nedir1-768x417.jpg 768w, https:\/\/www.markatescilsorgulama.net\/blog\/wp-content\/uploads\/2026\/07\/Machine-Learning-Nedir-Yapay-Zekadan-Farki-Nedir1.jpg 810w\" sizes=\"auto, (max-width: 592px) 100vw, 592px\" \/><\/span><\/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\/machine-learning-nedir\/#Machine_Learning_Nedir\" >Machine Learning Nedir?<\/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.markatescilsorgulama.net\/blog\/machine-learning-nedir\/#Machine_Learning_Nasil_Calisir\" >Machine Learning 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-3\" href=\"https:\/\/www.markatescilsorgulama.net\/blog\/machine-learning-nedir\/#Yapay_Zeka_Nedir\" >Yapay Zeka Nedir?<\/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.markatescilsorgulama.net\/blog\/machine-learning-nedir\/#Machine_Learning_ve_Yapay_Zeka_Arasindaki_Fark_Nedir\" >Machine Learning ve Yapay Zeka Aras\u0131ndaki Fark Nedir?<\/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.markatescilsorgulama.net\/blog\/machine-learning-nedir\/#Basit_Bir_Benzetme_ile_Aciklamak_Gerekirse\" >Basit Bir Benzetme ile A\u00e7\u0131klamak Gerekirse<\/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.markatescilsorgulama.net\/blog\/machine-learning-nedir\/#Machine_Learning_Turleri_Nelerdir\" >Machine Learning T\u00fcrleri Nelerdir?<\/a><\/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\/machine-learning-nedir\/#1_Denetimli_Ogrenme\" >1. Denetimli \u00d6\u011frenme<\/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\/machine-learning-nedir\/#2_Denetimsiz_Ogrenme\" >2. Denetimsiz \u00d6\u011frenme<\/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\/machine-learning-nedir\/#3_Pekistirmeli_Ogrenme\" >3. Peki\u015ftirmeli \u00d6\u011frenme<\/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\/machine-learning-nedir\/#Deep_Learning_ile_Machine_Learning_Arasindaki_Fark\" >Deep Learning ile Machine Learning Aras\u0131ndaki Fark<\/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\/machine-learning-nedir\/#Machine_Learning_Gunluk_Hayatta_Nerelerde_Kullanilir\" >Machine Learning G\u00fcnl\u00fck Hayatta Nerelerde Kullan\u0131l\u0131r?<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-12\" href=\"https:\/\/www.markatescilsorgulama.net\/blog\/machine-learning-nedir\/#Machine_Learning_Kullanim_Alanlari\" >Machine Learning 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-13\" href=\"https:\/\/www.markatescilsorgulama.net\/blog\/machine-learning-nedir\/#Isletmeler_Icin_Machine_Learning_Neden_Onemlidir\" >\u0130\u015fletmeler \u0130\u00e7in Machine Learning Neden \u00d6nemlidir?<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-14\" href=\"https:\/\/www.markatescilsorgulama.net\/blog\/machine-learning-nedir\/#Machine_Learningin_Avantajlari\" >Machine Learning\u2019in Avantajlar\u0131<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-15\" href=\"https:\/\/www.markatescilsorgulama.net\/blog\/machine-learning-nedir\/#Machine_Learningin_Sinirlamalari\" >Machine Learning\u2019in S\u0131n\u0131rlamalar\u0131<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-16\" href=\"https:\/\/www.markatescilsorgulama.net\/blog\/machine-learning-nedir\/#Machine_Learning_ve_Yapay_Zeka_Ornekleri\" >Machine Learning ve Yapay Zeka \u00d6rnekleri<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-17\" href=\"https:\/\/www.markatescilsorgulama.net\/blog\/machine-learning-nedir\/#Machine_Learning_SEO_ve_Dijital_Pazarlamada_Nasil_Kullanilir\" >Machine Learning SEO ve Dijital Pazarlamada Nas\u0131l Kullan\u0131l\u0131r?<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-18\" href=\"https:\/\/www.markatescilsorgulama.net\/blog\/machine-learning-nedir\/#Machine_Learning_Ogrenmek_Icin_Hangi_Kavramlari_Bilmek_Gerekir\" >Machine Learning \u00d6\u011frenmek \u0130\u00e7in Hangi Kavramlar\u0131 Bilmek Gerekir?<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-19\" href=\"https:\/\/www.markatescilsorgulama.net\/blog\/machine-learning-nedir\/#Machine_Learning_Gelecekte_Neden_Daha_Onemli_Olacak\" >Machine Learning Gelecekte Neden Daha \u00d6nemli Olacak?<\/a><\/li><\/ul><\/nav><\/div>\n<h2><span class=\"ez-toc-section\" id=\"Machine_Learning_Nedir\"><\/span><b>Machine Learning Nedir?<\/b><span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p><span style=\"font-weight: 400;\">Machine learning, T\u00fcrk\u00e7esiyle <\/span><b>makine \u00f6\u011frenmesi<\/b><span style=\"font-weight: 400;\">, bilgisayar sistemlerinin a\u00e7\u0131k\u00e7a programla nmadan verilerden \u00f6\u011frenmesini sa\u011flayan bir yapay zeka alt alan\u0131d\u0131r.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Klasik yaz\u0131l\u0131m mant\u0131\u011f\u0131nda bir geli\u015ftirici, bilgisayara ne yapmas\u0131 gerekti\u011fini kurallar halinde tek tek tan\u0131mlar. \u00d6rne\u011fin \u201ce\u011fer kullan\u0131c\u0131 \u015fifresini yanl\u0131\u015f girerse hata mesaj\u0131 g\u00f6ster\u201d gibi net komutlar yaz\u0131l\u0131r. Machine learning sistemlerinde ise bilgisayara sadece kurallar verilmez; bunun yerine b\u00fcy\u00fck miktarda veri sunulur ve sistem bu verilerden \u00f6r\u00fcnt\u00fcler \u00e7\u0131kararak karar vermeyi \u00f6\u011frenir.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Basit bir \u00f6rnekle a\u00e7\u0131klamak gerekirse:<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Bir e-posta servisinin spam mailleri ay\u0131rt etmesini istedi\u011fimizi d\u00fc\u015f\u00fcnelim. Klasik yaz\u0131l\u0131m yakla\u015f\u0131m\u0131nda spam kelimeleri tek tek tan\u0131mlamak gerekir. Ancak spam g\u00f6nderenler s\u00fcrekli farkl\u0131 kelimeler, ba\u015fl\u0131klar ve y\u00f6ntemler kullanabilir. Machine learning yakla\u015f\u0131m\u0131nda ise sisteme binlerce spam ve spam olmayan e-posta \u00f6rne\u011fi verilir. Sistem bu verileri analiz ederek hangi \u00f6zelliklerin spam olas\u0131l\u0131\u011f\u0131n\u0131 art\u0131rd\u0131\u011f\u0131n\u0131 \u00f6\u011frenir.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">B\u00f6ylece yeni bir e-posta geldi\u011finde, daha \u00f6nce g\u00f6rd\u00fc\u011f\u00fc \u00f6rneklere dayanarak bu e-postan\u0131n spam olup olmad\u0131\u011f\u0131n\u0131 tahmin edebilir.<\/span><\/p>\n<h2><span class=\"ez-toc-section\" id=\"Machine_Learning_Nasil_Calisir\"><\/span><b>Machine Learning Nas\u0131l \u00c7al\u0131\u015f\u0131r?<\/b><span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p><span style=\"font-weight: 400;\">Machine learning sistemleri temel olarak veriden \u00f6\u011frenir. Bu \u00f6\u011frenme s\u00fcreci birka\u00e7 ana ad\u0131mdan olu\u015fur.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">\u0130lk ad\u0131m <\/span><b>veri toplama<\/b><span style=\"font-weight: 400;\"> s\u00fcrecidir. Modelin \u00f6\u011frenebilmesi i\u00e7in yeterli miktarda ve kaliteli veriye ihtiya\u00e7 vard\u0131r. Bu veri m\u00fc\u015fteri davran\u0131\u015flar\u0131, g\u00f6rseller, metinler, sat\u0131\u015f kay\u0131tlar\u0131, web sitesi hareketleri, \u00fcr\u00fcn yorumlar\u0131 veya sens\u00f6r verileri olabilir.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">\u0130kinci ad\u0131m <\/span><b>veri haz\u0131rlama<\/b><span style=\"font-weight: 400;\"> a\u015famas\u0131d\u0131r. Toplanan veriler genellikle do\u011frudan kullan\u0131lmaya haz\u0131r de\u011fildir. Eksik, hatal\u0131, tekrar eden veya d\u00fczensiz veriler temizlenir. Bu a\u015fama machine learning projelerinin en kritik b\u00f6l\u00fcmlerinden biridir \u00e7\u00fcnk\u00fc modelin ba\u015far\u0131s\u0131 b\u00fcy\u00fck \u00f6l\u00e7\u00fcde veri kalitesine ba\u011fl\u0131d\u0131r.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">\u00dc\u00e7\u00fcnc\u00fc ad\u0131mda <\/span><b>model e\u011fitimi<\/b><span style=\"font-weight: 400;\"> yap\u0131l\u0131r. Model, kendisine verilen veriler \u00fczerinde \u00f6r\u00fcnt\u00fcler bulmaya \u00e7al\u0131\u015f\u0131r. \u00d6rne\u011fin bir e-ticaret sitesi i\u00e7in kullan\u0131c\u0131lar\u0131n ge\u00e7mi\u015f al\u0131\u015fveri\u015f davran\u0131\u015flar\u0131n\u0131 analiz ederek hangi kullan\u0131c\u0131n\u0131n hangi \u00fcr\u00fcn\u00fc sat\u0131n alma ihtimalinin y\u00fcksek oldu\u011funu \u00f6\u011frenebilir.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">D\u00f6rd\u00fcnc\u00fc ad\u0131m <\/span><b>test ve de\u011ferlendirme<\/b><span style=\"font-weight: 400;\"> a\u015famas\u0131d\u0131r. Modelin ger\u00e7ekten do\u011fru \u00f6\u011frenip \u00f6\u011frenmedi\u011fini anlamak i\u00e7in daha \u00f6nce g\u00f6rmedi\u011fi verilerle test yap\u0131l\u0131r. E\u011fer model yaln\u0131zca e\u011fitim verisini ezberlediyse, yeni verilerde ba\u015far\u0131s\u0131z olabilir. Bu nedenle modelin genelleme yapabilmesi \u00f6nemlidir.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Son ad\u0131m ise <\/span><b>tahmin veya karar \u00fcretme<\/b><span style=\"font-weight: 400;\"> a\u015famas\u0131d\u0131r. E\u011fitilen model, yeni veriler \u00fczerinde sonu\u00e7 \u00fcretmeye ba\u015flar. \u00d6rne\u011fin bir m\u00fc\u015fterinin \u00fcr\u00fcn\u00fc sat\u0131n alma ihtimalini tahmin eder, bir g\u00f6rseldeki nesneyi tan\u0131r veya bir metnin olumlu mu olumsuz mu oldu\u011funu s\u0131n\u0131fland\u0131r\u0131r.<\/span><\/p>\n<h2><span class=\"ez-toc-section\" id=\"Yapay_Zeka_Nedir\"><\/span><b>Yapay Zeka Nedir?<\/b><span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p><span style=\"font-weight: 400;\">Yapay zeka, bilgisayar sistemlerinin insan zekas\u0131na benzer g\u00f6revleri yerine getirebilmesini ama\u00e7layan geni\u015f bir teknoloji alan\u0131d\u0131r. Bu g\u00f6revler aras\u0131nda \u00f6\u011frenme, ak\u0131l y\u00fcr\u00fctme, problem \u00e7\u00f6zme, dil anlama, g\u00f6r\u00fcnt\u00fc tan\u0131ma, karar verme ve planlama gibi s\u00fcre\u00e7ler yer al\u0131r.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Yapay zeka, tek bir teknoloji ya da y\u00f6ntem de\u011fildir. Aksine farkl\u0131 teknikleri kapsayan geni\u015f bir \u015femsiye kavramd\u0131r. Machine learning, deep learning, do\u011fal dil i\u015fleme, bilgisayarl\u0131 g\u00f6r\u00fc, uzman sistemler ve robotik gibi pek \u00e7ok alan yapay zekan\u0131n i\u00e7inde de\u011ferlendirilebilir.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">\u00d6rne\u011fin bir m\u00fc\u015fteri hizmetleri chatbot\u2019u, kullan\u0131c\u0131n\u0131n sorusunu anlay\u0131p yan\u0131t verebiliyorsa bu bir yapay zeka uygulamas\u0131d\u0131r. Bir navigasyon uygulamas\u0131 trafik yo\u011funlu\u011funu analiz ederek en h\u0131zl\u0131 rotay\u0131 \u00f6neriyorsa bu da yapay zekadan yararlanan bir sistemdir.<\/span><\/p>\n<h2><span class=\"ez-toc-section\" id=\"Machine_Learning_ve_Yapay_Zeka_Arasindaki_Fark_Nedir\"><\/span><b>Machine Learning ve Yapay Zeka Aras\u0131ndaki Fark Nedir?<\/b><span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p><span style=\"font-weight: 400;\">Machine learning ve yapay zeka aras\u0131ndaki fark\u0131 anlaman\u0131n en kolay yolu, bu iki kavram\u0131n kapsam\u0131n\u0131 kar\u015f\u0131la\u015ft\u0131rmakt\u0131r.<\/span><\/p>\n<p><b>Yapay zeka daha geni\u015f bir kavramd\u0131r.<\/b><span style=\"font-weight: 400;\"> \u0130nsan benzeri zekaya sahip sistemler geli\u015ftirmeyi ama\u00e7layan t\u00fcm y\u00f6ntemleri kapsar.<\/span><\/p>\n<p><b>Machine learning ise yapay zekan\u0131n bir alt dal\u0131d\u0131r.<\/b><span style=\"font-weight: 400;\"> Bilgisayarlar\u0131n verilerden \u00f6\u011frenmesini ve \u00f6\u011frendikleri bilgilere g\u00f6re tahmin ya da karar \u00fcretmesini sa\u011flar.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Yani her machine learning uygulamas\u0131 bir yapay zeka uygulamas\u0131d\u0131r; ancak her yapay zeka uygulamas\u0131 machine learning kullanmak zorunda de\u011fildir.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">\u00d6rne\u011fin tamamen kurallara dayal\u0131 \u00e7al\u0131\u015fan eski tip bir uzman sistem de yapay zeka kapsam\u0131nda de\u011ferlendirilebilir. Bu sistem, \u201ce\u011fer \u015fu belirti varsa \u015fu sonucu \u00f6ner\u201d gibi sabit kurallarla \u00e7al\u0131\u015f\u0131r. Ancak verilerden \u00f6\u011frenmedi\u011fi i\u00e7in machine learning sistemi say\u0131lmaz.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Machine learning ise kurallar\u0131 manuel olarak yazmak yerine, sistemin verilerden kendi \u00f6r\u00fcnt\u00fclerini \u00f6\u011frenmesini sa\u011flar.<\/span><\/p>\n<p style=\"text-align: center;\"><span style=\"font-weight: 400;\"><img loading=\"lazy\" decoding=\"async\" class=\"alignnone  wp-image-1910\" src=\"https:\/\/www.markatescilsorgulama.net\/blog\/wp-content\/uploads\/2026\/07\/Machine-Learning-Nedir-Yapay-Zekadan-Farki-Nedir2-300x163.jpg\" alt=\"\" width=\"609\" height=\"331\" srcset=\"https:\/\/www.markatescilsorgulama.net\/blog\/wp-content\/uploads\/2026\/07\/Machine-Learning-Nedir-Yapay-Zekadan-Farki-Nedir2-300x163.jpg 300w, https:\/\/www.markatescilsorgulama.net\/blog\/wp-content\/uploads\/2026\/07\/Machine-Learning-Nedir-Yapay-Zekadan-Farki-Nedir2-768x417.jpg 768w, https:\/\/www.markatescilsorgulama.net\/blog\/wp-content\/uploads\/2026\/07\/Machine-Learning-Nedir-Yapay-Zekadan-Farki-Nedir2.jpg 810w\" sizes=\"auto, (max-width: 609px) 100vw, 609px\" \/><\/span><\/p>\n<h2><span class=\"ez-toc-section\" id=\"Basit_Bir_Benzetme_ile_Aciklamak_Gerekirse\"><\/span><b>Basit Bir Benzetme ile A\u00e7\u0131klamak Gerekirse<\/b><span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p><span style=\"font-weight: 400;\">Yapay zekay\u0131 b\u00fcy\u00fck bir teknoloji ailesi gibi d\u00fc\u015f\u00fcnebiliriz. Machine learning bu ailenin \u00f6nemli \u00fcyelerinden biridir.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Yapay zeka, bilgisayarlar\u0131n ak\u0131ll\u0131 davran\u0131\u015flar sergilemesini hedefler. Machine learning ise bu ak\u0131ll\u0131 davran\u0131\u015flar\u0131n veriden \u00f6\u011frenme yoluyla kazan\u0131lmas\u0131n\u0131 sa\u011flar.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">\u00d6rne\u011fin:<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Bir \u00e7ocu\u011fa kedinin ne oldu\u011funu \u00f6\u011fretmek i\u00e7in ona \u201ckedilerin iki kula\u011f\u0131, d\u00f6rt aya\u011f\u0131, b\u0131y\u0131klar\u0131 vard\u0131r\u201d gibi kurallar anlatabilirsiniz. Bu klasik programlama yakla\u015f\u0131m\u0131na benzer.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Ya da \u00e7ocu\u011fa y\u00fczlerce kedi foto\u011fraf\u0131 g\u00f6sterirsiniz. Zamanla \u00e7ocuk kedilerin ortak \u00f6zelliklerini fark eder ve daha \u00f6nce g\u00f6rmedi\u011fi bir kediyi de tan\u0131yabilir. Bu da machine learning yakla\u015f\u0131m\u0131na benzer.<\/span><\/p>\n<h2><span class=\"ez-toc-section\" id=\"Machine_Learning_Turleri_Nelerdir\"><\/span><b>Machine Learning T\u00fcrleri Nelerdir?<\/b><span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p><span style=\"font-weight: 400;\">Machine learning kendi i\u00e7inde farkl\u0131 \u00f6\u011frenme t\u00fcrlerine ayr\u0131l\u0131r. En yayg\u0131n kullan\u0131lan t\u00fcrler denetimli \u00f6\u011frenme, denetimsiz \u00f6\u011frenme ve peki\u015ftirmeli \u00f6\u011frenmedir.<\/span><\/p>\n<h2><span class=\"ez-toc-section\" id=\"1_Denetimli_Ogrenme\"><\/span><b>1. Denetimli \u00d6\u011frenme<\/b><span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p><span style=\"font-weight: 400;\">Denetimli \u00f6\u011frenme, modelin etiketlenmi\u015f verilerle e\u011fitildi\u011fi machine learning t\u00fcr\u00fcd\u00fcr. Burada sisteme hem veri hem de do\u011fru cevaplar verilir.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">\u00d6rne\u011fin bir modelin ev fiyatlar\u0131n\u0131 tahmin etmesini istiyorsak, ge\u00e7mi\u015f ev sat\u0131\u015f verilerini ve bu evlerin ger\u00e7ek sat\u0131\u015f fiyatlar\u0131n\u0131 modele veririz. Model; metrekare, konum, oda say\u0131s\u0131, bina ya\u015f\u0131 gibi \u00f6zelliklerle fiyat aras\u0131ndaki ili\u015fkiyi \u00f6\u011frenir.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Denetimli \u00f6\u011frenme \u015fu alanlarda s\u0131k\u00e7a kullan\u0131l\u0131r:<\/span><\/p>\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Sat\u0131\u015f tahmini<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Kredi risk analizi<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Spam e-posta tespiti<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">M\u00fc\u015fteri kayb\u0131 tahmini<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Hastal\u0131k te\u015fhisi<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">G\u00f6rsel s\u0131n\u0131fland\u0131rma<\/span><\/li>\n<\/ul>\n<h2><span class=\"ez-toc-section\" id=\"2_Denetimsiz_Ogrenme\"><\/span><b>2. Denetimsiz \u00d6\u011frenme<\/b><span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p><span style=\"font-weight: 400;\">Denetimsiz \u00f6\u011frenmede veriler etiketli de\u011fildir. Yani modele do\u011fru cevaplar verilmez. Model, veriler aras\u0131ndaki benzerlikleri ve \u00f6r\u00fcnt\u00fcleri kendi ba\u015f\u0131na ke\u015ffetmeye \u00e7al\u0131\u015f\u0131r.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">\u00d6rne\u011fin bir e-ticaret sitesi m\u00fc\u015fterilerini davran\u0131\u015flar\u0131na g\u00f6re gruplamak isteyebilir. Sistem; s\u0131k al\u0131\u015fveri\u015f yapanlar, indirim d\u00f6nemlerinde al\u0131\u015fveri\u015f yapanlar, belirli kategorilere ilgi duyanlar gibi segmentleri otomatik olarak ortaya \u00e7\u0131karabilir.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Denetimsiz \u00f6\u011frenme \u00f6zellikle \u015fu alanlarda kullan\u0131l\u0131r:<\/span><\/p>\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">M\u00fc\u015fteri segmentasyonu<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Davran\u0131\u015f analizi<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Anomali tespiti<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Veri k\u00fcmelerinin grupland\u0131r\u0131lmas\u0131<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Pazar ara\u015ft\u0131rmas\u0131<\/span><\/li>\n<\/ul>\n<h2><span class=\"ez-toc-section\" id=\"3_Pekistirmeli_Ogrenme\"><\/span><b>3. Peki\u015ftirmeli \u00d6\u011frenme<\/b><span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p><span style=\"font-weight: 400;\">Peki\u015ftirmeli \u00f6\u011frenme, bir sistemin deneme yan\u0131lma yoluyla en iyi aksiyonu \u00f6\u011frenmesine dayan\u0131r. Model, yapt\u0131\u011f\u0131 eylemler sonucunda \u00f6d\u00fcl veya ceza al\u0131r ve zamanla en y\u00fcksek \u00f6d\u00fcl\u00fc sa\u011flayan stratejiyi \u00f6\u011frenir.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Bu yakla\u015f\u0131m \u00f6zellikle oyunlar, robotik sistemler, otonom ara\u00e7lar ve dinamik karar s\u00fcre\u00e7lerinde kullan\u0131l\u0131r.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">\u00d6rne\u011fin bir oyun botu, oyunda hangi hamlelerin kazanmaya daha \u00e7ok katk\u0131 sa\u011flad\u0131\u011f\u0131n\u0131 deneyimleyerek \u00f6\u011frenebilir.<\/span><\/p>\n<h2><span class=\"ez-toc-section\" id=\"Deep_Learning_ile_Machine_Learning_Arasindaki_Fark\"><\/span><b>Deep Learning ile Machine Learning Aras\u0131ndaki Fark<\/b><span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p><span style=\"font-weight: 400;\">Machine learning ile birlikte s\u0131k duyulan bir di\u011fer kavram da <\/span><b>deep learning<\/b><span style=\"font-weight: 400;\">, yani <\/span><b>derin \u00f6\u011frenme<\/b><span style=\"font-weight: 400;\">dir.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Deep learning, machine learning\u2019in bir alt dal\u0131d\u0131r. \u0130nsan beynindeki sinir a\u011flar\u0131ndan ilham alan yapay sinir a\u011flar\u0131n\u0131 kullan\u0131r. \u00d6zellikle \u00e7ok b\u00fcy\u00fck veri setleriyle ve karma\u015f\u0131k problemlerle \u00e7al\u0131\u015f\u0131rken g\u00fc\u00e7l\u00fc sonu\u00e7lar verebilir.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">G\u00f6r\u00fcnt\u00fc tan\u0131ma, ses tan\u0131ma, do\u011fal dil i\u015fleme, \u00e7eviri sistemleri ve \u00fcretken yapay zeka uygulamalar\u0131nda deep learning yayg\u0131n olarak kullan\u0131l\u0131r.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">K\u0131saca ili\u015fki \u015fu \u015fekildedir:<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Yapay zeka en geni\u015f kavramd\u0131r. Machine learning yapay zekan\u0131n alt alan\u0131d\u0131r. Deep learning ise machine learning\u2019in daha \u00f6zel ve geli\u015fmi\u015f bir alt alan\u0131d\u0131r.<\/span><\/p>\n<h2><span class=\"ez-toc-section\" id=\"Machine_Learning_Gunluk_Hayatta_Nerelerde_Kullanilir\"><\/span><b>Machine Learning G\u00fcnl\u00fck Hayatta Nerelerde Kullan\u0131l\u0131r?<\/b><span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p><span style=\"font-weight: 400;\">Machine learning bug\u00fcn fark\u0131nda olmasak bile bir\u00e7ok dijital deneyimin i\u00e7inde yer al\u0131r.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">\u00d6rne\u011fin video izleme platformlar\u0131nda kar\u015f\u0131m\u0131za \u00e7\u0131kan \u00f6neriler machine learning algoritmalar\u0131yla olu\u015fturulur. Sistem, daha \u00f6nce izledi\u011fimiz i\u00e7erikleri, be\u011fenilerimizi, izleme s\u00fcremizi ve benzer kullan\u0131c\u0131lar\u0131n davran\u0131\u015flar\u0131n\u0131 analiz ederek bize yeni \u00f6neriler sunar.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">E-ticaret sitelerinde \u201cbunlar\u0131 da be\u011fenebilirsiniz\u201d veya \u201csizin i\u00e7in \u00f6nerilen \u00fcr\u00fcnler\u201d alanlar\u0131 da machine learning ile \u00e7al\u0131\u015fabilir. Kullan\u0131c\u0131 davran\u0131\u015flar\u0131 analiz edilerek sat\u0131n alma ihtimali y\u00fcksek \u00fcr\u00fcnler \u00f6ne \u00e7\u0131kar\u0131l\u0131r.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Bankac\u0131l\u0131kta doland\u0131r\u0131c\u0131l\u0131k tespiti i\u00e7in machine learning kullan\u0131l\u0131r. Sistem, ola\u011fan d\u0131\u015f\u0131 i\u015flem davran\u0131\u015flar\u0131n\u0131 tespit ederek riskli hareketleri belirleyebilir.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Sa\u011fl\u0131k sekt\u00f6r\u00fcnde g\u00f6r\u00fcnt\u00fc analizi, hastal\u0131k riski tahmini ve klinik karar destek sistemlerinde machine learning\u2019den yararlan\u0131l\u0131r.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Dijital pazarlamada ise hedef kitle segmentasyonu, reklam optimizasyonu, d\u00f6n\u00fc\u015f\u00fcm tahmini ve m\u00fc\u015fteri ya\u015fam boyu de\u011feri analizi gibi s\u00fcre\u00e7lerde machine learning \u00f6nemli rol oynar.<\/span><\/p>\n<h2><span class=\"ez-toc-section\" id=\"Machine_Learning_Kullanim_Alanlari\"><\/span><b>Machine Learning Kullan\u0131m Alanlar\u0131<\/b><span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p><span style=\"font-weight: 400;\">Machine learning\u2019in kullan\u0131m alanlar\u0131 olduk\u00e7a geni\u015ftir. \u0130\u015fletmeler, kamu kurumlar\u0131, teknoloji \u015firketleri, sa\u011fl\u0131k kurulu\u015flar\u0131 ve finansal kurumlar farkl\u0131 ihtiya\u00e7lar i\u00e7in bu teknolojiden yararlanabilir.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Ba\u015fl\u0131ca kullan\u0131m alanlar\u0131 \u015funlard\u0131r:<\/span><\/p>\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">\u00d6neri sistemleri<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Tahmine dayal\u0131 analiz<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">M\u00fc\u015fteri segmentasyonu<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Doland\u0131r\u0131c\u0131l\u0131k tespiti<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">G\u00f6r\u00fcnt\u00fc ve ses tan\u0131ma<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Do\u011fal dil i\u015fleme<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Chatbot ve sanal asistanlar<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Stok ve talep tahmini<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Fiyat optimizasyonu<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Risk analizi<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Ki\u015fiselle\u015ftirilmi\u015f pazarlama<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Siber g\u00fcvenlik<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">\u00dcretim s\u00fcre\u00e7lerinde kalite kontrol<\/span><\/li>\n<\/ul>\n<h2><span class=\"ez-toc-section\" id=\"Isletmeler_Icin_Machine_Learning_Neden_Onemlidir\"><\/span><b>\u0130\u015fletmeler \u0130\u00e7in Machine Learning Neden \u00d6nemlidir?<\/b><span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p><span style=\"font-weight: 400;\">Machine learning, i\u015fletmelerin veriyi daha etkili kullanmas\u0131n\u0131 sa\u011flar. G\u00fcn\u00fcm\u00fczde \u015firketler web siteleri, mobil uygulamalar, CRM sistemleri, sat\u0131\u015f kanallar\u0131, reklam platformlar\u0131 ve m\u00fc\u015fteri hizmetleri \u00fczerinden b\u00fcy\u00fck miktarda veri toplar. Ancak bu verilerin tek ba\u015f\u0131na var olmas\u0131 yeterli de\u011fildir. \u00d6nemli olan, veriyi anlaml\u0131 i\u00e7g\u00f6r\u00fclere d\u00f6n\u00fc\u015ft\u00fcrebilmektir.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Machine learning bu noktada i\u015fletmelere \u00f6nemli avantajlar sunar.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">\u0130lk olarak daha do\u011fru tahminler yap\u0131lmas\u0131n\u0131 sa\u011flar. \u00d6rne\u011fin sat\u0131\u015flar\u0131n hangi d\u00f6nemde artaca\u011f\u0131n\u0131, hangi m\u00fc\u015fterilerin sat\u0131n alma ihtimalinin y\u00fcksek oldu\u011funu veya hangi kullan\u0131c\u0131lar\u0131n markadan kopma riski ta\u015f\u0131d\u0131\u011f\u0131n\u0131 tahmin etmek m\u00fcmk\u00fcn olabilir.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">\u0130kinci olarak ki\u015fiselle\u015ftirme sa\u011flar. Kullan\u0131c\u0131lara ilgi alanlar\u0131na, davran\u0131\u015flar\u0131na ve ge\u00e7mi\u015f etkile\u015fimlerine g\u00f6re daha alakal\u0131 i\u00e7erikler, \u00fcr\u00fcnler veya kampanyalar sunulabilir.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">\u00dc\u00e7\u00fcnc\u00fc olarak operasyonel verimlilik sa\u011flar. Tekrarlayan analiz s\u00fcre\u00e7leri otomatikle\u015febilir, manuel karar s\u00fcre\u00e7leri h\u0131zlanabilir ve kaynaklar daha do\u011fru alanlara y\u00f6nlendirilebilir.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">D\u00f6rd\u00fcnc\u00fc olarak riskleri erken tespit etmeye yard\u0131mc\u0131 olur. Anormal i\u015flem davran\u0131\u015flar\u0131, sahtecilik giri\u015fimleri veya performans d\u00fc\u015f\u00fc\u015fleri daha h\u0131zl\u0131 fark edilebilir.<\/span><\/p>\n<h2><span class=\"ez-toc-section\" id=\"Machine_Learningin_Avantajlari\"><\/span><b>Machine Learning\u2019in Avantajlar\u0131<\/b><span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p><span style=\"font-weight: 400;\">Machine learning\u2019in en \u00f6nemli avantajlar\u0131ndan biri, b\u00fcy\u00fck veri setlerinden insan\u0131n manuel olarak fark etmesi zor olan \u00f6r\u00fcnt\u00fcleri \u00e7\u0131karabilmesidir. \u00d6zellikle y\u00fcksek hacimli ve karma\u015f\u0131k veri yap\u0131lar\u0131nda g\u00fc\u00e7l\u00fc sonu\u00e7lar \u00fcretebilir.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Bir di\u011fer avantaj\u0131 s\u00fcrekli geli\u015febilmesidir. Model yeni verilerle g\u00fcncellendik\u00e7e, de\u011fi\u015fen kullan\u0131c\u0131 davran\u0131\u015flar\u0131na veya piyasa ko\u015fullar\u0131na uyum sa\u011flayabilir.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Machine learning ayn\u0131 zamanda karar s\u00fcre\u00e7lerini h\u0131zland\u0131r\u0131r. Bir insan\u0131n saatlerce analiz ederek ula\u015faca\u011f\u0131 baz\u0131 sonu\u00e7lar, iyi e\u011fitilmi\u015f bir model taraf\u0131ndan \u00e7ok daha k\u0131sa s\u00fcrede \u00fcretilebilir.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Ki\u015fiselle\u015ftirme a\u00e7\u0131s\u0131ndan da b\u00fcy\u00fck katk\u0131 sa\u011flar. Dijital platformlar kullan\u0131c\u0131ya daha alakal\u0131 deneyimler sunarak memnuniyeti ve d\u00f6n\u00fc\u015f\u00fcm oranlar\u0131n\u0131 art\u0131rabilir.<\/span><\/p>\n<h2><span class=\"ez-toc-section\" id=\"Machine_Learningin_Sinirlamalari\"><\/span><b>Machine Learning\u2019in S\u0131n\u0131rlamalar\u0131<\/b><span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p><span style=\"font-weight: 400;\">Machine learning g\u00fc\u00e7l\u00fc bir teknoloji olsa da kusursuz de\u011fildir. En \u00f6nemli s\u0131n\u0131rlamalardan biri veri kalitesine ba\u011f\u0131ml\u0131 olmas\u0131d\u0131r. Yanl\u0131\u015f, eksik veya tarafl\u0131 verilerle e\u011fitilen modeller hatal\u0131 sonu\u00e7lar \u00fcretebilir.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Bir di\u011fer \u00f6nemli konu yorumlanabilirliktir. Baz\u0131 machine learning modelleri, \u00f6zellikle deep learning modelleri, kararlar\u0131n\u0131 nas\u0131l verdi\u011fini a\u00e7\u0131klamakta zorlanabilir. Bu durum finans, sa\u011fl\u0131k ve hukuk gibi y\u00fcksek hassasiyet gerektiren alanlarda \u00f6nemli bir soru i\u015fareti yaratabilir.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Machine learning sistemleri ayr\u0131ca ge\u00e7mi\u015f verilere dayan\u0131r. E\u011fer gelecek, ge\u00e7mi\u015ften \u00e7ok farkl\u0131 \u015fekilde geli\u015firse modelin tahminleri zay\u0131flayabilir.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Bunun yan\u0131nda gizlilik, etik, veri g\u00fcvenli\u011fi ve reg\u00fclasyon uyumu da machine learning projelerinde dikkat edilmesi gereken konular aras\u0131ndad\u0131r.<\/span><\/p>\n<h2><span class=\"ez-toc-section\" id=\"Machine_Learning_ve_Yapay_Zeka_Ornekleri\"><\/span><b>Machine Learning ve Yapay Zeka \u00d6rnekleri<\/b><span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p><span style=\"font-weight: 400;\">Bir sistemin yapay zeka m\u0131 yoksa machine learning mi oldu\u011funu anlamak i\u00e7in sistemin nas\u0131l \u00e7al\u0131\u015ft\u0131\u011f\u0131na bakmak gerekir.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">\u00d6rne\u011fin sesli asistanlar yapay zeka uygulamalar\u0131d\u0131r. Kullan\u0131c\u0131n\u0131n sesini metne \u00e7evirir, niyetini anlamaya \u00e7al\u0131\u015f\u0131r ve uygun yan\u0131t\u0131 \u00fcretir. Bu s\u00fcre\u00e7te machine learning ve deep learning modelleri kullan\u0131labilir.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Bir kural tabanl\u0131 chatbot ise yapay zeka kapsam\u0131na girebilir; ancak yaln\u0131zca \u00f6nceden tan\u0131mlanm\u0131\u015f cevaplara g\u00f6re \u00e7al\u0131\u015f\u0131yorsa machine learning kullanm\u0131yor olabilir.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Netflix, YouTube veya Spotify gibi platformlar\u0131n \u00f6neri sistemleri machine learning \u00f6rnekleridir. Kullan\u0131c\u0131 davran\u0131\u015flar\u0131n\u0131 analiz ederek ki\u015fiye \u00f6zel \u00f6neriler \u00fcretirler.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Bir bankan\u0131n sahte i\u015flem tespit sistemi de machine learning kullanabilir. Sistem, normal i\u015flem davran\u0131\u015flar\u0131n\u0131 \u00f6\u011frenir ve bu davran\u0131\u015flardan sapan i\u015flemleri riskli olarak i\u015faretleyebilir.<\/span><\/p>\n<h2><span class=\"ez-toc-section\" id=\"Machine_Learning_SEO_ve_Dijital_Pazarlamada_Nasil_Kullanilir\"><\/span><b>Machine Learning SEO ve Dijital Pazarlamada Nas\u0131l Kullan\u0131l\u0131r?<\/b><span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p><span style=\"font-weight: 400;\">Machine learning, SEO ve dijital pazarlama alan\u0131nda da giderek daha \u00f6nemli hale gelmektedir.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">SEO taraf\u0131nda arama motorlar\u0131, kullan\u0131c\u0131 niyetini anlamak, i\u00e7erik kalitesini de\u011ferlendirmek ve arama sonu\u00e7lar\u0131n\u0131 ki\u015fiselle\u015ftirmek i\u00e7in yapay zeka ve machine learning y\u00f6ntemlerinden yararlan\u0131r. Bu nedenle i\u00e7erik \u00fcretiminde yaln\u0131zca anahtar kelime kullan\u0131m\u0131na odaklanmak yeterli de\u011fildir. Kullan\u0131c\u0131n\u0131n ger\u00e7ek ihtiyac\u0131n\u0131 kar\u015f\u0131layan, g\u00fcvenilir, kapsaml\u0131 ve iyi yap\u0131land\u0131r\u0131lm\u0131\u015f i\u00e7erikler daha \u00f6nemli hale gelir.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Dijital reklamc\u0131l\u0131kta machine learning, teklif stratejileri, hedefleme, d\u00f6n\u00fc\u015f\u00fcm tahmini ve reklam optimizasyonu i\u00e7in kullan\u0131l\u0131r. Reklam platformlar\u0131, hangi kullan\u0131c\u0131n\u0131n d\u00f6n\u00fc\u015f\u00fcm ger\u00e7ekle\u015ftirme ihtimalinin daha y\u00fcksek oldu\u011funu tahmin ederek b\u00fct\u00e7eyi daha verimli kullanmaya \u00e7al\u0131\u015f\u0131r.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">E-posta pazarlamas\u0131nda ise kullan\u0131c\u0131lar\u0131n a\u00e7ma, t\u0131klama ve sat\u0131n alma davran\u0131\u015flar\u0131na g\u00f6re ki\u015fiselle\u015ftirilmi\u015f kampanyalar olu\u015fturulabilir.<\/span><\/p>\n<h2><span class=\"ez-toc-section\" id=\"Machine_Learning_Ogrenmek_Icin_Hangi_Kavramlari_Bilmek_Gerekir\"><\/span><b>Machine Learning \u00d6\u011frenmek \u0130\u00e7in Hangi Kavramlar\u0131 Bilmek Gerekir?<\/b><span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p><span style=\"font-weight: 400;\">Machine learning \u00f6\u011frenmek isteyenlerin baz\u0131 temel kavramlara a\u015fina olmas\u0131 faydal\u0131d\u0131r.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Bunlar\u0131n ba\u015f\u0131nda veri, algoritma, model, e\u011fitim verisi, test verisi, \u00f6zellikler, etiketler, do\u011fruluk, hata oran\u0131 ve tahmin gibi kavramlar gelir.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Ayr\u0131ca istatistik, olas\u0131l\u0131k, temel programlama bilgisi ve veri analizi konular\u0131na hakim olmak machine learning\u2019i anlamay\u0131 kolayla\u015ft\u0131r\u0131r.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Python, machine learning alan\u0131nda en yayg\u0131n kullan\u0131lan programlama dillerinden biridir. NumPy, pandas, scikit-learn, TensorFlow ve PyTorch gibi k\u00fct\u00fcphaneler bu alanda s\u0131k\u00e7a tercih edilir.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Ancak herkesin teknik uzman olmas\u0131 gerekmez. \u0130\u015fletme y\u00f6neticileri, pazarlama ekipleri ve \u00fcr\u00fcn ekipleri i\u00e7in machine learning\u2019in temel mant\u0131\u011f\u0131n\u0131 bilmek, veriye dayal\u0131 karar s\u00fcre\u00e7lerini daha iyi y\u00f6netmek a\u00e7\u0131s\u0131ndan yeterli olabilir.<\/span><\/p>\n<h2><span class=\"ez-toc-section\" id=\"Machine_Learning_Gelecekte_Neden_Daha_Onemli_Olacak\"><\/span><b>Machine Learning Gelecekte Neden Daha \u00d6nemli Olacak?<\/b><span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p><span style=\"font-weight: 400;\">Dijital d\u00fcnyada \u00fcretilen veri miktar\u0131 her ge\u00e7en g\u00fcn art\u0131yor. Kullan\u0131c\u0131 davran\u0131\u015flar\u0131, cihazlar, web siteleri, mobil uygulamalar, sens\u00f6rler ve dijital platformlar s\u00fcrekli veri \u00fcretiyor. Bu verinin anlamland\u0131r\u0131lmas\u0131 ise \u015firketler i\u00e7in \u00f6nemli bir rekabet avantaj\u0131 yarat\u0131yor.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Machine learning, bu b\u00fcy\u00fck veri ak\u0131\u015f\u0131n\u0131 analiz ederek daha h\u0131zl\u0131, daha do\u011fru ve daha ki\u015fiselle\u015ftirilmi\u015f kararlar al\u0131nmas\u0131n\u0131 sa\u011flayabilir.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Gelecekte m\u00fc\u015fteri deneyimi, otomasyon, sa\u011fl\u0131k teknolojileri, finansal analiz, \u00fcretim, siber g\u00fcvenlik, e\u011fitim ve pazarlama gibi alanlarda machine learning\u2019in daha da yayg\u0131nla\u015fmas\u0131 beklenmektedir.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">\u00d6zellikle \u00fcretken yapay zeka ara\u00e7lar\u0131n\u0131n geli\u015fmesiyle birlikte machine learning ve deep learning teknolojileri daha g\u00f6r\u00fcn\u00fcr hale gelmi\u015ftir. Metin yazan, g\u00f6rsel olu\u015fturan, kod \u00fcreten veya kullan\u0131c\u0131larla do\u011fal dilde konu\u015fabilen sistemlerin arkas\u0131nda b\u00fcy\u00fck \u00f6l\u00e7\u00fcde bu teknolojiler yer al\u0131r.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Machine learning, bilgisayar sistemlerinin verilerden \u00f6\u011frenerek tahmin, s\u0131n\u0131fland\u0131rma veya karar \u00fcretmesini sa\u011flayan bir yapay zeka alt alan\u0131d\u0131r. Yapay zeka daha geni\u015f bir kavramken, machine learning bu kavram\u0131n i\u00e7inde yer alan ve veriden \u00f6\u011frenmeye odaklanan \u00f6nemli bir teknolojidir.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">K\u0131saca ifade etmek gerekirse, yapay zeka bilgisayarlar\u0131n ak\u0131ll\u0131 davran\u0131\u015flar sergilemesini hedefler; machine learning ise bu ak\u0131ll\u0131 davran\u0131\u015flar\u0131n verilerden \u00f6\u011frenme yoluyla kazan\u0131lmas\u0131n\u0131 sa\u011flar.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Bug\u00fcn \u00f6neri sistemlerinden dijital reklamlara, bankac\u0131l\u0131ktan sa\u011fl\u0131\u011fa, e-ticaretten siber g\u00fcvenli\u011fe kadar pek \u00e7ok alanda machine learning kullan\u0131lmaktad\u0131r. \u0130\u015fletmeler i\u00e7in machine learning, veriyi daha anlaml\u0131 hale getirme, m\u00fc\u015fteri deneyimini geli\u015ftirme, riskleri azaltma ve daha do\u011fru kararlar alma konusunda b\u00fcy\u00fck f\u0131rsatlar sunar.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Bu nedenle machine learning yaln\u0131zca teknik ekiplerin ilgilenmesi gereken bir konu de\u011fildir. Dijital d\u00fcnyada rekabet\u00e7i kalmak isteyen her i\u015fletme i\u00e7in anla\u015f\u0131lmas\u0131 gereken temel teknolojilerden biridir.<\/span><\/p>\n<p>Benzer blog yaz\u0131lar\u0131n\u0131 <a href=\"https:\/\/www.markatescilsorgulama.net\/blog\">buradan<\/a> g\u00f6r\u00fcnt\u00fcleyebilirsiniz.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Yapay zeka son y\u0131llar\u0131n en \u00e7ok konu\u015fulan teknolojilerinden biri haline geldi. Chatbot\u2019lardan \u00f6neri sistemlerine, g\u00f6r\u00fcnt\u00fc tan\u0131madan sesli asistanlara kadar pek \u00e7ok dijital deneyimin arkas\u0131nda yapay zeka teknolojileri yer al\u0131yor. Ancak bu alanda s\u0131k\u00e7a kar\u0131\u015ft\u0131r\u0131lan iki kavram var: yapay zeka ve machine learning, yani makine \u00f6\u011frenmesi. Peki machine learning nedir? Yapay zekadan fark\u0131 nedir? Her yapay [&hellip;]<\/p>\n","protected":false},"author":7,"featured_media":1911,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[44],"tags":[],"class_list":["post-1908","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-marka-tescil"],"views":5,"_links":{"self":[{"href":"https:\/\/www.markatescilsorgulama.net\/blog\/wp-json\/wp\/v2\/posts\/1908","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\/7"}],"replies":[{"embeddable":true,"href":"https:\/\/www.markatescilsorgulama.net\/blog\/wp-json\/wp\/v2\/comments?post=1908"}],"version-history":[{"count":1,"href":"https:\/\/www.markatescilsorgulama.net\/blog\/wp-json\/wp\/v2\/posts\/1908\/revisions"}],"predecessor-version":[{"id":1912,"href":"https:\/\/www.markatescilsorgulama.net\/blog\/wp-json\/wp\/v2\/posts\/1908\/revisions\/1912"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.markatescilsorgulama.net\/blog\/wp-json\/wp\/v2\/media\/1911"}],"wp:attachment":[{"href":"https:\/\/www.markatescilsorgulama.net\/blog\/wp-json\/wp\/v2\/media?parent=1908"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.markatescilsorgulama.net\/blog\/wp-json\/wp\/v2\/categories?post=1908"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.markatescilsorgulama.net\/blog\/wp-json\/wp\/v2\/tags?post=1908"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}