{"id":90197,"date":"2025-03-03T15:11:44","date_gmt":"2025-03-03T07:11:44","guid":{"rendered":"https:\/\/solomon-3d.mesvr.tw\/?p=90197"},"modified":"2025-07-18T16:44:40","modified_gmt":"2025-07-18T08:44:40","slug":"makine-ogrenimi-nedir","status":"publish","type":"post","link":"https:\/\/solomon-3d.mesvr.tw\/tr\/blog\/makine-ogrenimi-nedir\/","title":{"rendered":"Makine \u00d6\u011frenimi Nedir?"},"content":{"rendered":"
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Makine \u00d6\u011frenimi Nedir?<\/h1><\/div>\n\n\n\n
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Makine \u00d6\u011frenimine Giri\u015f<\/strong><\/h2>\n\n\n\n
Makine \u00f6\u011frenimi, yapay zekan\u0131n<\/a> bir alt k\u00fcmesi olup, bilgisayarlar\u0131n verilerden \u00f6\u011frenmesini sa\u011flamaya odaklan\u0131r, bunun i\u00e7in bilgisayarlar\u0131n a\u00e7\u0131k\u00e7a programlanmas\u0131na gerek yoktur. Ba\u015fka bir deyi\u015fle, makine \u00f6\u011frenimi, makinelerin deneyimlerinden \u00f6\u011frenip geli\u015fmesini \u00f6\u011fretme y\u00f6ntemidir, t\u0131pk\u0131 insanlar\u0131n yapt\u0131\u011f\u0131 gibi. Makine \u00f6\u011freniminin yayg\u0131n uygulamalar\u0131 aras\u0131nda, kullan\u0131c\u0131lar\u0131n ilgi alanlar\u0131na ve aktivitelerine g\u00f6re arkada\u015flar\u0131, gruplar\u0131 ve i\u00e7erikleri \u00f6neren Facebook ve di\u011fer sosyal medya platformlar\u0131 yer al\u0131r. Bu sadece buzda\u011f\u0131n\u0131n g\u00f6r\u00fcnen k\u0131sm\u0131 olsa da, makine \u00f6\u011frenimi t\u0131p tan\u0131s\u0131, menkul k\u0131ymet analizi, parmak izi tan\u0131ma, konu\u015fma i\u015fleme, online al\u0131\u015fveri\u015f, hava tahmini ve daha bir\u00e7ok alanda giderek daha fazla \u00f6nem kazanmaktad\u0131r.<\/div>\n<\/div>\n<\/div>\n <\/div><\/div>\n\n\n\n
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Makine \u00d6\u011frenimi Nas\u0131l \u00c7al\u0131\u015f\u0131r?<\/h2>\n\n\n\n
Makine \u00f6\u011freniminin temel fikri, verilerden \u00f6\u011frenebilen algoritmalar olu\u015fturmak ve ard\u0131ndan bu bilgiyi yeni veriler hakk\u0131nda tahminler yapmak veya kararlar almak i\u00e7in kullanmakt\u0131r. Bu s\u00fcre\u00e7 birka\u00e7 ad\u0131mdan olu\u015fur:<\/div>\n\n\n\n
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Veri Toplama<\/h3>\n\n\n\n

\u0130lk ad\u0131m, algoritmay\u0131 e\u011fitmek i\u00e7in kullan\u0131labilecek verilerin toplanmas\u0131d\u0131r. Bu veriler, sens\u00f6rler, veritabanlar\u0131 veya kullan\u0131c\u0131 etkile\u015fimleri gibi \u00e7e\u015fitli kaynaklardan gelebilir.<\/p>\n<\/div>\n<\/div>\n\n\n\n

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Veri \u00d6n \u0130\u015fleme<\/h3>\n\n\n\n

Veri topland\u0131ktan sonra, makine \u00f6\u011frenimi algoritmas\u0131 taraf\u0131ndan kullan\u0131labilir hale getirilmesi i\u00e7in \u00f6n i\u015fleme yap\u0131lmal\u0131d\u0131r. Bu, verilerin temizlenmesini, alakas\u0131z bilgilerin kald\u0131r\u0131lmas\u0131n\u0131 ve verilerin kolayca i\u015flenebilecek bir formata d\u00f6n\u00fc\u015ft\u00fcr\u00fclmesini i\u00e7erebilir.<\/p>\n<\/div>\n<\/div>\n\n\n\n

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Model E\u011fitimi<\/h3>\n\n\n\n

Sonraki ad\u0131m, \u00f6n i\u015flenmi\u015f veri \u00fczerinde makine \u00f6\u011frenimi modelinin e\u011fitilmesidir. E\u011fitim s\u0131ras\u0131nda, algoritma verilerdeki desenleri tan\u0131may\u0131 \u00f6\u011frenir ve bu desenlere dayanarak tahminlerde bulunur.<\/p>\n<\/div>\n<\/div>\n\n\n\n

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Model de\u011ferlendirme<\/h3>\n\n\n\n

Model e\u011fitildikten sonra, yeni veriler \u00fczerinde nas\u0131l performans g\u00f6sterdi\u011fini belirlemek i\u00e7in de\u011ferlendirilmesi gerekir. Bu, modelin e\u011fitim s\u0131ras\u0131nda kullan\u0131lmayan ayr\u0131 bir veri k\u00fcmesi \u00fczerinde test edilmesiyle yap\u0131l\u0131r.<\/p>\n<\/div>\n<\/div>\n\n\n\n

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Model Yay\u0131nlama<\/h3>\n\n\n\n

Son olarak, e\u011fitilen model yay\u0131nlan\u0131r ve yeni veriler hakk\u0131nda tahminlerde bulunmak veya kararlar almak i\u00e7in kullan\u0131l\u0131r.<\/p>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n <\/div><\/div>\n\n\n\n

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Makine \u00d6\u011frenimi T\u00fcrleri<\/h2>\n\n\n\n
Makine \u00f6\u011frenimi, genellikle yapay zeka ba\u011flam\u0131nda tart\u0131\u015f\u0131lsa da, t\u00fcm yapay zeka uygulamalar\u0131 makine \u00f6\u011frenimini i\u00e7ermez. Makine \u00f6\u011frenimi, insan \u00f6\u011frenimine benzer \u015fekilde, desenleri tan\u0131mak ve tahminlerde bulunmak i\u00e7in e\u011fitim verilerine ihtiya\u00e7 duyar. Makine \u00f6\u011frenimi d\u00f6rt t\u00fcre ayr\u0131l\u0131r: denetimli \u00f6\u011frenme<\/strong>, denetimsiz \u00f6\u011frenme<\/strong>, yar\u0131 denetimli \u00f6\u011frenme<\/strong> ve takviye \u00f6\u011frenme<\/strong>.<\/div>\n\n\n\n
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Denetimli \u00d6\u011frenme<\/strong><\/h3>\n\n\n\n
Denetimli \u00f6\u011frenme, verileri etiketleyerek makineye do\u011fru cevaplar\u0131 nas\u0131l tan\u0131yaca\u011f\u0131n\u0131 \u00f6\u011fretmeyi i\u00e7eren bir makine \u00f6\u011frenimi tekni\u011fidir. \u00d6rne\u011fin, kediler ve k\u00f6pekler i\u00e7in g\u00f6r\u00fcnt\u00fc tan\u0131ma durumunda, ilk olarak insanlar taraf\u0131ndan kedileri ve k\u00f6pekleri ay\u0131rt eden \u00f6zellikler (kulaklar, bacaklar, v\u00fccut \u015fekli gibi) etiketlenmelidir. Makine, ard\u0131ndan verileri analiz ederek desenleri tan\u0131r ve tahminlerde bulunur. Denetimli \u00f6\u011frenme, y\u00fcksek do\u011fruluk sa\u011flamak i\u00e7in b\u00fcy\u00fck miktarda veri gerektirir, ancak etiketlenmi\u015f verilerin bol oldu\u011fu g\u00f6revlerde etkilidir.<\/div>\n\n\n\n
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Denetimsiz \u00d6\u011frenme<\/h3>\n\n\n\n
Kelimenin anlam\u0131na g\u00f6re, denetimsiz \u00f6\u011frenme, makineye \u00f6nceden etiketlenmi\u015f e\u011fitim \u00f6rnekleri sunmadan e\u011fitim verme i\u015flemidir. Bunun yerine, makine verinin \u00f6zelliklerini otomatik olarak tan\u0131mak ve s\u0131n\u0131fland\u0131rmak i\u00e7in b\u0131rak\u0131l\u0131r. \u00d6rne\u011fin, bir makineye kediler ve k\u00f6peklerin b\u00fcy\u00fck say\u0131da g\u00f6r\u00fcnt\u00fcs\u00fc verilebilir, ancak \u00f6nceden hangi g\u00f6r\u00fcnt\u00fclerin kedi oldu\u011funu ve hangilerinin k\u00f6pek oldu\u011funu \u00f6\u011frenmesine gerek yoktur. Makine, ard\u0131ndan otomatik olarak potansiyel kedi ve k\u00f6pek \u00f6zelliklerini ay\u0131rt eder ve bunlar\u0131 buna g\u00f6re s\u0131n\u0131fland\u0131r\u0131r. Denetimsiz \u00f6\u011frenmenin yayg\u0131n i\u015flevleri aras\u0131nda k\u00fcmeleme, ili\u015fkilendirme ve boyut indirgeme bulunur. Bu ara\u00e7lar, veri madencili\u011fi s\u00fcrecinin erken a\u015famalar\u0131nda veri ke\u015ffi i\u00e7in kullan\u0131\u015fl\u0131d\u0131r. Denetimsiz \u00f6\u011frenme y\u00f6ntemleri, insan girdisi konusunda daha az talepkar olsa da, AI modelleri i\u00e7in sorunlar yaratabilir. \u00c7\u00fcnk\u00fc alakas\u0131z \u00f6zellikler fazla \u00f6nemsenebilir ve bu da \u00f6nyarg\u0131l\u0131 tahmin sonu\u00e7lar\u0131na yol a\u00e7abilir.<\/div>\n<\/div>\n<\/div>\n<\/div>\n\n\n\n
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Yar\u0131 Denetimli \u00d6\u011frenme<\/h3>\n\n\n\n
Yar\u0131 denetimli \u00f6\u011frenme, makine \u00f6\u011frenimi yarg\u0131lar\u0131na bir standart sa\u011flamak amac\u0131yla verilerin k\u00fc\u00e7\u00fck bir k\u0131sm\u0131n\u0131 etiketlemeyi i\u00e7erir. Bu y\u00f6ntem, daha do\u011fru tahminler yap\u0131lmas\u0131n\u0131 sa\u011flar ve \u015fu anda en yayg\u0131n kullan\u0131lan makine \u00f6\u011frenimi t\u00fcr\u00fcd\u00fcr. \u00d6rne\u011fin, kediler ve k\u00f6peklerin 100 g\u00f6r\u00fcnt\u00fcs\u00fcnden rastgele bir se\u00e7im yap\u0131labilir ve bu g\u00f6r\u00fcnt\u00fclerden 10’u etiketlenerek makineye kedi ve k\u00f6pek \u00f6zellikleri hakk\u0131nda bilgi verilebilir. Makine, ard\u0131ndan bu 10 etiketli g\u00f6r\u00fcnt\u00fcy\u00fc referans alarak, g\u00f6r\u00fcnt\u00fclerdeki \u00f6zellikler aras\u0131ndaki ili\u015fkiyi kendi ba\u015f\u0131na tan\u0131may\u0131 \u00f6\u011frenir. Genellikle, yar\u0131 denetimli \u00f6\u011frenme ile yap\u0131lan makine tahminleri, denetimsiz \u00f6\u011frenmeye g\u00f6re daha do\u011fru olur.<\/div>\n<\/div>\n\n\n\n
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Takviye \u00d6\u011frenme<\/h3>\n\n\n\n
Takviye \u00f6\u011frenmesinin i\u015fleyi\u015fi, istenen sonu\u00e7lara ula\u015fmay\u0131 \u00f6\u011frenmek i\u00e7in \u00e7evreyle do\u011frudan etkile\u015fime girmeyi i\u00e7erir. Bu \u00f6\u011frenme y\u00f6ntemi, etiketleme gerektirmez, ancak bilgisayara hangi eylemlerin do\u011fru, hangilerinin yanl\u0131\u015f oldu\u011funu s\u00f6yleyerek, makinenin hatalar\u0131ndan \u00f6\u011frenmesini ve hedeflerine ula\u015fmada giderek daha verimli hale gelmesini sa\u011flar. Denetimsiz \u00f6\u011frenme ba\u011flam\u0131nda, takviye \u00f6\u011frenme \u00f6zellikle \u00f6nemlidir. \u00d6rne\u011fin, makine kendili\u011finden farkl\u0131 \u00f6zellikleri tan\u0131may\u0131 \u00f6\u011frenirken, yanl\u0131\u015fl\u0131kla bir k\u00f6pek foto\u011fraf\u0131n\u0131 kedi olarak tan\u0131mlarsa, bir insan taraf\u0131ndan hatadan \u00f6\u011frenmesi ve do\u011fru s\u0131n\u0131fland\u0131rma yetene\u011fini art\u0131rmas\u0131 sa\u011flanabilir. Bu da daha do\u011fru ve g\u00fcvenilir tahminlerle sonu\u00e7lan\u0131r.<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n <\/div><\/div>\n\n\n\n
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Makine \u00d6\u011frenmesinin Uygulamalar\u0131<\/h2>\n\n\n\n
Makine \u00f6\u011freniminin bir\u00e7ok alanda geni\u015f bir uygulama yelpazesi bulunmaktad\u0131r:<\/div>\n\n\n\n
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G\u00f6r\u00fcnt\u00fc Tan\u0131ma<\/h3>\n\n\n\n
Makine \u00f6\u011frenimi algoritmalar\u0131, g\u00f6r\u00fcnt\u00fclerdeki nesneleri, insanlar\u0131 ve di\u011fer \u00f6zellikleri tan\u0131mak i\u00e7in e\u011fitilebilir. Bu teknoloji, g\u00fcvenlik kameralar\u0131, otomatik etiketleme ve di\u011fer g\u00f6r\u00fcnt\u00fc tan\u0131ma sistemlerinde yayg\u0131n olarak kullan\u0131l\u0131r.<\/div>\n\n\n\n

Do\u011fal Dil \u0130\u015fleme<\/h3>\n\n\n\n
Makine \u00f6\u011frenimi, insan dilini analiz etmek ve anlamak i\u00e7in kullan\u0131labilir. Bu, sohbet robotlar\u0131, sesli asistanlar ve dil \u00e7eviri sistemleri gibi uygulamalar\u0131n geli\u015ftirilmesini sa\u011flar.<\/div>\n\n\n\n

Tahmine Dayal\u0131 Analiz<\/h3>\n\n\n\n
Makine \u00f6\u011frenimi algoritmalar\u0131, ge\u00e7mi\u015f verilere dayal\u0131 olarak gelecekteki olaylar\u0131 veya davran\u0131\u015flar\u0131 tahmin etmek i\u00e7in kullan\u0131labilir. Bu, finansal piyasa tahminlerinden m\u00fc\u015fteri davran\u0131\u015flar\u0131na kadar bir\u00e7ok alanda uygulanabilir.<\/div>\n\n\n\n

Doland\u0131r\u0131c\u0131l\u0131k Tespiti<\/h3>\n\n\n\n
Makine \u00f6\u011frenimi, finansal i\u015flemlerde doland\u0131r\u0131c\u0131l\u0131\u011f\u0131 tespit etmek ve \u00f6nlemek i\u00e7in kullan\u0131labilir. Anomalileri ve \u015f\u00fcpheli faaliyetleri belirleyerek, g\u00fcvenlik \u00f6nlemlerini g\u00fc\u00e7lendirebilir.<\/div>\n\n\n\n

T\u0131bbi Tan\u0131<\/h3>\n\n\n\n
Makine \u00f6\u011frenimi algoritmalar\u0131, t\u0131bbi g\u00f6r\u00fcnt\u00fcleri analiz etmek ve hastal\u0131klar\u0131 te\u015fhis etmek i\u00e7in e\u011fitilebilir. Bu, erken tan\u0131 ve tedavi s\u00fcre\u00e7lerinde b\u00fcy\u00fck bir potansiyel ta\u015f\u0131r.<\/div>\n<\/div>\n<\/div>\n <\/div><\/div>\n\n\n\n
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Makine \u00d6\u011frenimi \u00d6zeti<\/h2>\n\n\n\n
Makine \u00f6\u011frenimi, karma\u015f\u0131k problemleri \u00e7\u00f6zme bi\u00e7imimizi devrim niteli\u011finde de\u011fi\u015ftiren g\u00fc\u00e7l\u00fc bir ara\u00e7t\u0131r. Bilgisayarlar\u0131n verilerden \u00f6\u011frenmesini sa\u011flayarak, insanlar\u0131n tek ba\u015f\u0131na yapamayaca\u011f\u0131 tahminler ve kararlar alabilen algoritmalar olu\u015fturabiliriz. Ger\u00e7ekten de, bahsedilen d\u00f6rt makine \u00f6\u011frenimi t\u00fcr\u00fc\u2014denetimli \u00f6\u011frenme, denetimsiz \u00f6\u011frenme, yar\u0131-denetimli \u00f6\u011frenme ve peki\u015ftirmeli \u00f6\u011frenme\u2014yaln\u0131zca kaba s\u0131n\u0131fland\u0131rmalard\u0131r. Bir projede hangi algoritman\u0131n kullan\u0131laca\u011f\u0131, mevcut veri miktar\u0131 ve projenin hedefleri gibi bir\u00e7ok fakt\u00f6re ba\u011fl\u0131d\u0131r. Bu nedenle, \u00f6\u011frenme y\u00f6nteminden ba\u011f\u0131ms\u0131z olarak, ilk d\u00fc\u015f\u00fcn\u00fclmesi gereken soru her zaman \u2018Hangi problemi \u00e7\u00f6zmeye \u00e7al\u0131\u015f\u0131yoruz?\u2019 olmal\u0131d\u0131r.<\/div>\n<\/div>\n<\/div>\n <\/div><\/div>\n\n\n\n
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Makine \u00f6\u011frenimini aksiyon halinde g\u00f6rmek ister misiniz? Vaka \u00e7al\u0131\u015fmalar\u0131m\u0131z\u0131 ke\u015ffedin<\/strong><\/strong><\/span><\/span><\/span><\/a><\/div>\n<\/div>\n<\/div>\n <\/div><\/div>\n\n\n\n
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\"graphic<\/div>\n<\/div>\n<\/div>\n <\/div><\/div>","protected":false},"excerpt":{"rendered":"

Makine \u00d6\u011frenimi hakk\u0131nda bilgi edinin, bu, bilgisayarlar\u0131n verilerden \u00f6\u011frenmesini sa\u011flayan bir yapay zeka t\u00fcr\u00fcd\u00fcr. Bu yaz\u0131, ML’in temellerini, nas\u0131l \u00e7al\u0131\u015ft\u0131\u011f\u0131n\u0131 ve ML kullan\u0131m alanlar\u0131n\u0131 kapsar.<\/p>","protected":false},"author":875,"featured_media":89336,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"_gspb_post_css":"#gspb_row-id-gsbp-c005443{justify-content:space-between;margin-top:0;margin-bottom:0;display:flex;flex-wrap:wrap;min-height:250px;padding:0;overflow:hidden;background-size:cover;background-repeat:no-repeat;background-position:50% 68%;background-image:url(https:\/\/solomon-3d.mesvr.tw\/wp-content\/uploads\/2024\/01\/\u2014Pngtree\u2014technological-sense-geometric-line-simple_932581-1.jpg);filter:brightness(1) contrast(1) grayscale(0)}#gspb_row-id-gsbp-c005443>.gspb_row__content{display:flex;justify-content:space-between;margin:0 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