{"id":28183,"date":"2025-08-24T14:30:27","date_gmt":"2025-08-24T11:30:27","guid":{"rendered":"https:\/\/fatihsoysal.com\/blog\/r-ile-sinir-aglari-bastan-sona-kapsamli-bir-rehber\/"},"modified":"2025-08-24T14:30:27","modified_gmt":"2025-08-24T11:30:27","slug":"r-ile-sinir-aglari-bastan-sona-kapsamli-bir-rehber","status":"publish","type":"post","link":"https:\/\/fatihsoysal.com\/blog\/r-ile-sinir-aglari-bastan-sona-kapsamli-bir-rehber\/","title":{"rendered":"R ile Sinir A\u011flar\u0131: Ba\u015ftan Sona Kapsaml\u0131 Bir Rehber"},"content":{"rendered":"

R ile Sinir A\u011flar\u0131: Ba\u015ftan Sona Kapsaml\u0131 Bir Rehber<\/p>\n

Karma\u015f\u0131k veri k\u00fcmelerinden anlaml\u0131 i\u00e7g\u00f6r\u00fcler \u00e7\u0131karmak, g\u00fcn\u00fcm\u00fcz d\u00fcnyas\u0131nda hayati \u00f6nem ta\u015f\u0131yor. Bu i\u00e7g\u00f6r\u00fcleri elde etmek i\u00e7in g\u00fc\u00e7l\u00fc bir ara\u00e7 olan sinir a\u011flar\u0131, R programlama diliyle birle\u015fti\u011finde, veri analizi ve makine \u00f6\u011frenmesinde devrim yarat\u0131yor. Bu rehber, R kullanarak sinir a\u011flar\u0131n\u0131 s\u0131f\u0131rdan ileri seviyeye kadar ad\u0131m ad\u0131m \u00f6\u011frenmenizi sa\u011flayacak, ger\u00e7ek d\u00fcnya \u00f6rnekleriyle zenginle\u015ftirilmi\u015f kapsaml\u0131 bir yolculu\u011fa \u00e7\u0131kar\u0131yor.<\/p>\n

R’de Sinir A\u011flar\u0131na Giri\u015f: Temel Kavramlar Nelerdir?<\/h2>\n

Sinir a\u011flar\u0131, insan beyninin i\u015fleyi\u015finden ilham alan karma\u015f\u0131k algoritmalard\u0131r. Bir\u00e7ok basit i\u015flem biriminin (n\u00f6ron) birbirine ba\u011fl\u0131 oldu\u011fu bir a\u011f yap\u0131s\u0131yla \u00e7al\u0131\u015f\u0131rlar. Bu n\u00f6ronlar, verileri i\u015fleyerek, a\u011f\u0131rl\u0131kland\u0131r\u0131lm\u0131\u015f ba\u011flant\u0131lar arac\u0131l\u0131\u011f\u0131yla bilgi aktar\u0131rlar. \u00d6\u011frenme s\u00fcreci, bu a\u011f\u0131rl\u0131klar\u0131n, a\u011f\u0131n girdi ve \u00e7\u0131kt\u0131 verileri aras\u0131ndaki ili\u015fkiyi en iyi \u015fekilde modelleyecek \u015fekilde ayarlanmas\u0131yla ger\u00e7ekle\u015fir. R’de, neuralnet<\/code>, nnet<\/code>, ve keras<\/code> gibi paketler, sinir a\u011f\u0131 modellemesini kolayla\u015ft\u0131r\u0131r. Bu paketler, farkl\u0131 a\u011f mimarileri (\u00f6rne\u011fin, \u00e7ok katmanl\u0131 perceptronlar, geri yay\u0131l\u0131m algoritmas\u0131) ve optimizasyon teknikleri sunar. Ba\u015flang\u0131\u00e7ta, basit bir perceptron modeliyle ba\u015flayarak, daha karma\u015f\u0131k modellerin nas\u0131l \u00e7al\u0131\u015ft\u0131\u011f\u0131n\u0131 anlamak \u00f6nemlidir. \u00d6rne\u011fin, tek bir gizli katmana sahip bir \u00e7ok katmanl\u0131 perceptron, karma\u015f\u0131k, do\u011frusal olmayan ili\u015fkileri modelleme yetene\u011fine sahiptir. Her katman, bir \u00f6nceki katmandan ald\u0131\u011f\u0131 bilgileri i\u015fler ve bir sonraki katmana iletir. Son katman, a\u011f\u0131n tahminini veya s\u0131n\u0131fland\u0131rmas\u0131n\u0131 \u00fcretir.<\/p>\n

R’de Sinir A\u011f\u0131 Kurulumu: Gerekli Paketleri Nas\u0131l Y\u00fckleyebilirim?<\/h2>\n

R’de sinir a\u011f\u0131 modelleri olu\u015fturmak i\u00e7in \u00f6ncelikle gerekli paketleri y\u00fcklememiz gerekiyor. En yayg\u0131n kullan\u0131lan paketlerden baz\u0131lar\u0131 \u015funlard\u0131r: neuralnet<\/code>, nnet<\/code>, keras<\/code> ve tensorflow<\/code>. Bu paketleri CRAN’den (Comprehensive R Archive Network) kolayca y\u00fckleyebilirsiniz. A\u015fa\u011f\u0131daki kod blo\u011fu, neuralnet<\/code> paketinin nas\u0131l y\u00fcklendi\u011fini g\u00f6sterir:<\/p>\n

# neuralnet paketini y\u00fckleme\nif(!require(neuralnet)){install.packages(\"neuralnet\")}\nlibrary(neuralnet)<\/pre>\n
<\/code><\/p>\n
Bu ad\u0131m tamamland\u0131ktan sonra,  \u00e7e\u015fitli sinir a\u011f\u0131 modelleri olu\u015fturmak i\u00e7in bu paketlerin fonksiyonlar\u0131n\u0131 kullanabilirsiniz.  \u00d6rne\u011fin, neuralnet()<\/code> fonksiyonu, neuralnet<\/code> paketinde bir \u00e7ok katmanl\u0131 perceptron olu\u015fturmak i\u00e7in kullan\u0131l\u0131r.  nnet<\/code> paketi ise, daha h\u0131zl\u0131 ve verimli bir \u015fekilde sinir a\u011f\u0131 modelleri e\u011fitmek i\u00e7in optimizasyon algoritmalar\u0131 sunar.  keras<\/code> ve tensorflow<\/code> paketleri ise, daha geli\u015fmi\u015f derin \u00f6\u011frenme modelleri olu\u015fturmak i\u00e7in kullan\u0131labilen g\u00fc\u00e7l\u00fc ara\u00e7lard\u0131r.  Bu paketlerin her birinin kendine \u00f6zg\u00fc fonksiyonlar\u0131 ve parametreleri vard\u0131r ve bunlar\u0131 detayl\u0131 bir \u015fekilde \u00f6\u011frenmek, ba\u015far\u0131l\u0131 bir sinir a\u011f\u0131 modellemesi i\u00e7in kritik \u00f6neme sahiptir.<\/p>\n
Basit Bir Sinir A\u011f\u0131 Modeli Olu\u015fturma: Ad\u0131m Ad\u0131m Uygulama<\/h2>\n
\u015eimdi, basit bir \u00f6rnek \u00fczerinde, R kullanarak bir sinir a\u011f\u0131 modeli nas\u0131l olu\u015fturulaca\u011f\u0131n\u0131 g\u00f6sterelim.  Bu \u00f6rnekte,  iris veri k\u00fcmesini kullanarak \u00e7i\u00e7ek t\u00fcrlerini s\u0131n\u0131fland\u0131ran bir model e\u011fitece\u011fiz.  \u0130lk olarak, iris veri k\u00fcmesini y\u00fcklememiz ve \u00f6n i\u015fleme yapmam\u0131z gerekir.  Ard\u0131ndan, neuralnet()<\/code> fonksiyonunu kullanarak sinir a\u011f\u0131m\u0131z\u0131 olu\u015fturaca\u011f\u0131z.  A\u015fa\u011f\u0131daki kod, bu i\u015flemleri ad\u0131m ad\u0131m g\u00f6sterir:<\/p>\n
# iris veri k\u00fcmesini y\u00fckleme\ndata(iris)\n\n# veri k\u00fcmesini \u00f6l\u00e7eklendirme\niris_scaled <- scale(iris[,1:4])\n\n# hedef de\u011fi\u015fkeni (Species) fakt\u00f6r tipinde d\u00f6n\u00fc\u015ft\u00fcrme\niris_scaled <- cbind(iris_scaled, Species = as.numeric(iris$Species))\n\n# sinir a\u011f\u0131 modelini olu\u015fturma\nmodel <- neuralnet(Species ~ Sepal.Length + Sepal.Width + Petal.Length + Petal.Width,\n                   data = iris_scaled, hidden = c(5,3), linear.output = FALSE)\n\n# modelin performans\u0131n\u0131 de\u011ferlendirme\nprint(model$result.matrix)\nplot(model)<\/pre>\n
<\/code><\/p>\n
Bu kodda, hidden = c(5,3)<\/code> parametresi, a\u011f\u0131m\u0131z\u0131n iki gizli katman\u0131ndan olu\u015ftu\u011funu ve birinci katman\u0131n 5, ikinci katman\u0131n 3 n\u00f6rona sahip oldu\u011funu belirtir.  linear.output = FALSE<\/code> parametresi, modelin s\u0131n\u0131fland\u0131rma problemi i\u00e7in kullan\u0131ld\u0131\u011f\u0131n\u0131 belirtir. Modelin \u00e7\u0131kt\u0131s\u0131, a\u011f\u0131rl\u0131klar ve hata matrisi gibi bilgileri i\u00e7erir.  plot(model)<\/code> fonksiyonu, a\u011f\u0131n yap\u0131s\u0131n\u0131 g\u00f6rselle\u015ftirmemizi sa\u011flar.  Bu basit \u00f6rnek, R'de bir sinir a\u011f\u0131 modelinin nas\u0131l olu\u015fturulaca\u011f\u0131n\u0131 g\u00f6sterir. Daha karma\u015f\u0131k modeller olu\u015fturmak i\u00e7in, farkl\u0131 a\u011f mimarileri, optimizasyon teknikleri ve hiperparametre ayarlar\u0131 deneyebilirsiniz.<\/p>\n
R'de Sinir A\u011f\u0131 E\u011fitimi: Optimizasyon Teknikleri ve Hiperparametre Ayar\u0131<\/h2>\n
Bir sinir a\u011f\u0131n\u0131n ba\u015far\u0131s\u0131, b\u00fcy\u00fck \u00f6l\u00e7\u00fcde e\u011fitim s\u00fcrecinde kullan\u0131lan optimizasyon tekniklerine ve hiperparametre ayarlar\u0131na ba\u011fl\u0131d\u0131r.  Optimizasyon teknikleri, a\u011f\u0131n a\u011f\u0131rl\u0131klar\u0131n\u0131 g\u00fcncelleyerek hata fonksiyonunu en aza indirmeyi ama\u00e7lar.  Yayg\u0131n olarak kullan\u0131lan teknikler aras\u0131nda geri yay\u0131l\u0131m algoritmas\u0131, gradyan ini\u015fi ve Adam optimizasyon algoritmas\u0131 bulunur. Hiperparametreler ise, a\u011f\u0131n mimarisini ve e\u011fitim s\u00fcrecini kontrol eden parametrelerdir.  Bunlar aras\u0131nda gizli katman say\u0131s\u0131, n\u00f6ron say\u0131s\u0131, \u00f6\u011frenme oran\u0131, iterasyon say\u0131s\u0131 ve durma kriterleri yer al\u0131r.  \u0130deal hiperparametreler, veri k\u00fcmesine ve probleme \u00f6zg\u00fcd\u00fcr ve genellikle deneysel olarak belirlenir.  neuralnet<\/code>, nnet<\/code> ve keras<\/code> paketleri, farkl\u0131 optimizasyon teknikleri ve hiperparametre ayarlar\u0131n\u0131 destekler.  \u00d6rne\u011fin, neuralnet<\/code> fonksiyonunda learningrate<\/code>, algorithm<\/code> ve stepmax<\/code> gibi parametreleri ayarlayarak e\u011fitim s\u00fcrecini kontrol edebilirsiniz.  Do\u011fru hiperparametreleri bulmak i\u00e7in \u00e7apraz do\u011frulama gibi teknikleri kullanabilir ve performans\u0131 izleyerek en iyi sonu\u00e7lar\u0131 elde edebilirsiniz.  Uygun hiperparametre ayarlar\u0131, modelin a\u015f\u0131r\u0131 \u00f6\u011frenmeyi \u00f6nlemesine ve genelleme performans\u0131n\u0131 iyile\u015ftirmesine yard\u0131mc\u0131 olur.<\/p>\n
Ger\u00e7ek D\u00fcnya Senaryolar\u0131: Vaka Analizi<\/h2>\n
Sinir a\u011flar\u0131, \u00e7e\u015fitli alanlarda ger\u00e7ek d\u00fcnya problemlerini \u00e7\u00f6zmek i\u00e7in kullan\u0131l\u0131r.  \u00d6rne\u011fin, finans sekt\u00f6r\u00fcnde hisse senedi fiyatlar\u0131n\u0131 tahmin etmek, sa\u011fl\u0131k sekt\u00f6r\u00fcnde hastal\u0131klar\u0131 te\u015fhis etmek, pazarlamada m\u00fc\u015fteri davran\u0131\u015flar\u0131n\u0131 analiz etmek i\u00e7in kullan\u0131labilirler.  Bir vaka analizi olarak, m\u00fc\u015fteri churn oran\u0131n\u0131 tahmin etmek i\u00e7in bir sinir a\u011f\u0131 modelinin nas\u0131l kullan\u0131labilece\u011fini ele alal\u0131m.  Bir telekom\u00fcnikasyon \u015firketinin m\u00fc\u015fteri verilerini kullanarak, hangi m\u00fc\u015fterilerin hizmeti iptal etme olas\u0131l\u0131\u011f\u0131n\u0131n y\u00fcksek oldu\u011funu tahmin edebiliriz.  Bu veri k\u00fcmesi, m\u00fc\u015fterilerin demografik bilgilerini, kullan\u0131m al\u0131\u015fkanl\u0131klar\u0131n\u0131 ve faturaland\u0131rma bilgilerini i\u00e7erebilir.  Bir sinir a\u011f\u0131 modeli e\u011fiterek, bu \u00f6zelliklere dayanarak churn oran\u0131n\u0131 tahmin edebilir ve risk alt\u0131ndaki m\u00fc\u015fterileri belirleyebiliriz.  Bu, \u015firketin hedefli pazarlama kampanyalar\u0131yla m\u00fc\u015fteri kayb\u0131n\u0131 \u00f6nlemesine yard\u0131mc\u0131 olabilir.  Ba\u015fka bir \u00f6rnek olarak, bir g\u00f6r\u00fcnt\u00fc tan\u0131ma sisteminde,  keras<\/code> paketi ile CNN (Convolutional Neural Network) kullan\u0131larak, farkl\u0131 nesneleri s\u0131n\u0131fland\u0131rmak i\u00e7in bir model e\u011fitilebilir.  Bu, otonom s\u00fcr\u00fc\u015f sistemlerinden t\u0131bbi g\u00f6r\u00fcnt\u00fc analizine kadar bir\u00e7ok uygulamada kullan\u0131labilir. Bu uygulamalarda performans\u0131 de\u011ferlendirmek i\u00e7in hassasiyet, duyarl\u0131l\u0131k, F1 puan\u0131 gibi metrikleri kullanabiliriz.  Farkl\u0131 modellerin performans\u0131n\u0131 kar\u015f\u0131la\u015ft\u0131rmak i\u00e7in de bunlardan yararlanabiliriz.   Daha fazla bilgi i\u00e7in  [https:\/\/fatihsoysal.com](https:\/\/fatihsoysal.com) adresini ziyaret edebilirsiniz.<\/p>\n
\u0130leri D\u00fczey Teknikler: Derin \u00d6\u011frenme ve Keras ile Modelleme<\/h2>\n
Temel sinir a\u011flar\u0131 kavramlar\u0131n\u0131 anlad\u0131ktan sonra, derin \u00f6\u011frenme tekniklerini ke\u015ffetmek i\u00e7in harika bir f\u0131rsat\u0131n\u0131z var.  Derin \u00f6\u011frenme, \u00e7ok say\u0131da katmana sahip derin sinir a\u011flar\u0131 kullanarak karma\u015f\u0131k veri k\u00fcmelerinden bilgi \u00e7\u0131karmay\u0131 ama\u00e7layan bir makine \u00f6\u011frenmesi alt alan\u0131d\u0131r.  R'de, keras<\/code> ve tensorflow<\/code> paketleri, derin \u00f6\u011frenme modellerini olu\u015fturmak ve e\u011fitmek i\u00e7in g\u00fc\u00e7l\u00fc ara\u00e7lar sunar.  keras<\/code>, kullan\u0131c\u0131 dostu bir aray\u00fczle, \u00e7e\u015fitli derin \u00f6\u011frenme mimarilerini (\u00f6rne\u011fin, CNN, RNN, LSTM) kolayca uygulaman\u0131z\u0131 sa\u011flar.  Bir CNN, g\u00f6r\u00fcnt\u00fc tan\u0131ma ve i\u015fleme i\u00e7in idealdir, oysa bir RNN (Recursive Neural Network) veya LSTM (Long Short-Term Memory) modelleri, zaman serisi verileri analizinde kullan\u0131l\u0131r.  Bu modeller, derin \u00f6\u011frenmenin g\u00fcc\u00fcyle \u00e7ok daha karma\u015f\u0131k sorunlar\u0131 \u00e7\u00f6zmenize olanak tan\u0131r.  \u00d6rne\u011fin, do\u011fal dil i\u015flemede,  s\u00f6zc\u00fck vekt\u00f6rleri ve RNN'ler kullanarak, metin s\u0131n\u0131fland\u0131rma veya makine \u00e7evirisi gibi g\u00f6revler yap\u0131labilir.  \u0130leri d\u00fczey teknikler kullan\u0131rken, a\u015f\u0131r\u0131 \u00f6\u011frenme, model karma\u015f\u0131kl\u0131\u011f\u0131n\u0131 kontrol etme ve verilerin \u00f6n i\u015flenmesi gibi konulara dikkat etmek \u00f6nemlidir.  A\u015f\u0131r\u0131 \u00f6\u011frenmeyi \u00f6nlemek i\u00e7in, d\u00fczenleme teknikleri (\u00f6rne\u011fin, dropout, L1\/L2 d\u00fczenleme) ve erken durdurma y\u00f6ntemleri kullan\u0131labilir.  Karma\u015f\u0131k modellerin e\u011fitimi uzun zaman alabilir, bu nedenle performans iyile\u015ftirmeleri i\u00e7in GPU kullan\u0131m\u0131 da de\u011ferlendirilmelidir.<\/p>\n
Model De\u011ferlendirme ve Kar\u015f\u0131la\u015ft\u0131rma: Performans Metrikleri<\/h2>\n
E\u011fitti\u011finiz sinir a\u011f\u0131 modelinin performans\u0131n\u0131 de\u011ferlendirmek, modelin ba\u015far\u0131s\u0131n\u0131 anlamak ve iyile\u015ftirmeler yapmak i\u00e7in \u00e7ok \u00f6nemlidir.  Bunun i\u00e7in farkl\u0131 performans metrikleri kullan\u0131l\u0131r.  S\u0131n\u0131fland\u0131rma problemleri i\u00e7in hassasiyet, duyarl\u0131l\u0131k, \u00f6zg\u00fcll\u00fck, F1 skoru ve AUC (Alan Alt\u0131ndaki E\u011fri) gibi metrikler kullan\u0131l\u0131r.  Regresyon problemleri i\u00e7inse, ortalama kare hatas\u0131 (MSE), ortalama mutlak hata (MAE) ve R-kare gibi metrikler kullan\u0131l\u0131r.  Farkl\u0131 modellerin performans\u0131n\u0131 kar\u015f\u0131la\u015ft\u0131rmak i\u00e7in ayn\u0131 metrikleri kullanman\u0131z \u00f6nemlidir.  Ayr\u0131ca, modelin genelleme yetene\u011fini de\u011ferlendirmek i\u00e7in e\u011fitim verileriyle ve test verileriyle elde edilen performans sonu\u00e7lar\u0131n\u0131 kar\u015f\u0131la\u015ft\u0131rmak gereklidir.  E\u011fer test verileri \u00fczerindeki performans, e\u011fitim verileri \u00fczerindeki performanstan \u00f6nemli \u00f6l\u00e7\u00fcde d\u00fc\u015f\u00fckse, modelin a\u015f\u0131r\u0131 \u00f6\u011frenme problemi ya\u015fad\u0131\u011f\u0131 anlam\u0131na gelir.  Bu durumda, modelin karma\u015f\u0131kl\u0131\u011f\u0131n\u0131 azaltmak, d\u00fczenleme teknikleri uygulamak veya daha fazla veri kullanmak gibi \u00e7\u00f6z\u00fcmler denenebilir.  Modelin performans\u0131n\u0131 iyile\u015ftirmek i\u00e7in, farkl\u0131 hiperparametre de\u011ferleri denemek, farkl\u0131 a\u011f mimarileri kullanmak ve farkl\u0131 \u00f6n i\u015fleme teknikleri uygulamak gibi ad\u0131mlar at\u0131labilir.  Sonu\u00e7 olarak, performans metriklerinin do\u011fru kullan\u0131m\u0131 ve yorumlanmas\u0131, etkili bir sinir a\u011f\u0131 modeli olu\u015fturmada kritik bir ad\u0131md\u0131r.<\/p>\n
Sonu\u00e7 ve S\u0131k\u00e7a Sorulan Sorular<\/h2>\n
Bu rehberde, R kullanarak sinir a\u011flar\u0131n\u0131n nas\u0131l olu\u015fturulaca\u011f\u0131, e\u011fitilce\u011fi ve de\u011ferlendirilece\u011fi ad\u0131m ad\u0131m a\u00e7\u0131klanm\u0131\u015ft\u0131r.  Basit \u00f6rneklerden ileri d\u00fczey tekniklere kadar geni\u015f bir yelpazede konu anlat\u0131lm\u0131\u015ft\u0131r.  Ger\u00e7ek d\u00fcnya senaryolar\u0131 ve vaka analizleri ile konunun uygulamalar\u0131 vurgulanm\u0131\u015ft\u0131r.  Sinir a\u011flar\u0131,  veri analizi ve makine \u00f6\u011frenmesinde g\u00fc\u00e7l\u00fc bir ara\u00e7t\u0131r ve bu rehber, R ile sinir a\u011flar\u0131n\u0131 kullanmaya ba\u015flamak i\u00e7in sa\u011flam bir temel olu\u015fturmay\u0131 ama\u00e7lamaktad\u0131r. Daha fazla derinlemesine bilgi i\u00e7in [https:\/\/fatihsoysal.com](https:\/\/fatihsoysal.com) sitesini ziyaret edebilirsiniz.<\/p>\n
S\u0131k\u00e7a Sorulan Sorular:<\/h3>\n
    \n
  • Sinir a\u011flar\u0131 hangi t\u00fcr problemler i\u00e7in uygundur?<\/strong> Sinir a\u011flar\u0131, s\u0131n\u0131fland\u0131rma, regresyon, k\u00fcmeleme ve zaman serisi analizi gibi bir\u00e7ok farkl\u0131 problem t\u00fcr\u00fc i\u00e7in uygundur.  Karma\u015f\u0131k, do\u011frusal olmayan ili\u015fkileri modelleme yetene\u011fine sahiptirler.<\/li>\n
  • A\u015f\u0131r\u0131 \u00f6\u011frenmeyi nas\u0131l \u00f6nleyebilirim?<\/strong> A\u015f\u0131r\u0131 \u00f6\u011frenmeyi \u00f6nlemek i\u00e7in d\u00fczenleme teknikleri (dropout, L1\/L2 d\u00fczenleme), erken durdurma, daha fazla veri kullan\u0131m\u0131 ve model karma\u015f\u0131kl\u0131\u011f\u0131n\u0131 azaltma gibi y\u00f6ntemler kullan\u0131labilir.<\/li>\n
  • Hangi optimizasyon algoritmas\u0131n\u0131 kullanmal\u0131y\u0131m?<\/strong> En uygun optimizasyon algoritmas\u0131, veri k\u00fcmesine ve probleme ba\u011fl\u0131d\u0131r.  Adam, RMSprop ve SGD gibi algoritmalar yayg\u0131n olarak kullan\u0131l\u0131r.  Deney yaparak en iyi performans\u0131 veren algoritmay\u0131 belirlemek \u00f6nemlidir.<\/li>\n
  • Gizli katman say\u0131s\u0131 ve n\u00f6ron say\u0131s\u0131n\u0131 nas\u0131l belirlemeliyim?<\/strong> Gizli katman say\u0131s\u0131 ve n\u00f6ron say\u0131s\u0131, genellikle deneysel olarak belirlenir.  Ba\u015flang\u0131\u00e7ta k\u00fc\u00e7\u00fck bir say\u0131 ile ba\u015flay\u0131p, performans\u0131 izleyerek kademeli olarak art\u0131rabilirsiniz.  \u00c7ok fazla katman ve n\u00f6ron kullanmak, a\u015f\u0131r\u0131 \u00f6\u011frenmeye neden olabilir.<\/li>\n
  • R'de sinir a\u011f\u0131 modellemesi i\u00e7in en iyi paket hangisidir?<\/strong>  neuralnet<\/code>, nnet<\/code> ve keras<\/code> paketleri pop\u00fcler ve g\u00fc\u00e7l\u00fc se\u00e7eneklerdir.  Se\u00e7ti\u011finiz paket, projenizin karma\u015f\u0131kl\u0131\u011f\u0131na ve ihtiya\u00e7lar\u0131n\u0131za ba\u011fl\u0131 olmal\u0131d\u0131r.<\/li>\n<\/ul>\n
    Yazar: Fatih Soysal<\/p>\n","protected":false},"excerpt":{"rendered":"R ile Sinir A\u011flar\u0131: Ba\u015ftan Sona Kapsaml\u0131 Bir Rehber Karma\u015f\u0131k veri k\u00fcmelerinden anlaml\u0131 i\u00e7g\u00f6r\u00fcler \u00e7\u0131karmak, g\u00fcn\u00fcm\u00fcz d\u00fcnyas\u0131nda hayati…","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"csco_page_header_type":"","csco_page_load_nextpost":"","csco_page_subscribe_form":"","csco_page_contact_form":"","footnotes":""},"categories":[1],"tags":[],"class_list":{"0":"post-28183","1":"post","2":"type-post","3":"status-publish","4":"format-standard","6":"category-genel","7":"cs-entry","8":"cs-video-wrap"},"yoast_head":"\nR ile Sinir A\u011flar\u0131: Ba\u015ftan Sona Kapsaml\u0131 Bir Rehber<\/title>\n<meta name=\"description\" content=\"Karma\u015f\u0131k veri k\u00fcmelerinden anlaml\u0131 i\u00e7g\u00f6r\u00fcler \u00e7\u0131karmak, g\u00fcn\u00fcm\u00fcz d\u00fcnyas\u0131nda hayati \u00f6nem ta\u015f\u0131yor. Bu i\u00e7g\u00f6r\u00fcleri elde etmek i\u00e7in g\u00fc\u00e7l\u00fc bir ara\u00e7 olan sinir a\u011flar\u0131, R programlama diliyle birle\u015fti\u011finde, veri analizi ve makine \u00f6\u011frenmesinde devrim yarat\u0131yor. Bu rehber, R kullanarak sinir a\u011flar\u0131n\u0131 s\u0131f\u0131rdan ileri seviyeye kadar ad\u0131m ad\u0131m \u00f6\u011frenmenizi sa\u011flayacak, ger\u00e7ek d\u00fcnya \u00f6rnekleriyle zenginle\u015ftirilmi\u015f kapsaml\u0131 bir yolculu\u011fa \u00e7\u0131kar\u0131yor.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/fatihsoysal.com\/blog\/r-ile-sinir-aglari-bastan-sona-kapsamli-bir-rehber\/\" \/>\n<meta property=\"og:locale\" content=\"tr_TR\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"R ile Sinir A\u011flar\u0131: Ba\u015ftan Sona Kapsaml\u0131 Bir Rehber\" \/>\n<meta property=\"og:description\" content=\"Karma\u015f\u0131k veri k\u00fcmelerinden anlaml\u0131 i\u00e7g\u00f6r\u00fcler \u00e7\u0131karmak, g\u00fcn\u00fcm\u00fcz d\u00fcnyas\u0131nda hayati \u00f6nem ta\u015f\u0131yor. Bu i\u00e7g\u00f6r\u00fcleri elde etmek i\u00e7in g\u00fc\u00e7l\u00fc bir ara\u00e7 olan sinir a\u011flar\u0131, R programlama diliyle birle\u015fti\u011finde, veri analizi ve makine \u00f6\u011frenmesinde devrim yarat\u0131yor. Bu rehber, R kullanarak sinir a\u011flar\u0131n\u0131 s\u0131f\u0131rdan ileri seviyeye kadar ad\u0131m ad\u0131m \u00f6\u011frenmenizi sa\u011flayacak, ger\u00e7ek d\u00fcnya \u00f6rnekleriyle zenginle\u015ftirilmi\u015f kapsaml\u0131 bir yolculu\u011fa \u00e7\u0131kar\u0131yor.\" \/>\n<meta property=\"og:url\" content=\"https:\/\/fatihsoysal.com\/blog\/r-ile-sinir-aglari-bastan-sona-kapsamli-bir-rehber\/\" \/>\n<meta property=\"og:site_name\" content=\"Kodlar\u0131n Gizemli D\u00fcnyas\u0131\" \/>\n<meta property=\"article:published_time\" content=\"2025-08-24T11:30:27+00:00\" \/>\n<meta name=\"author\" content=\"Fatih Soysal\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:label1\" content=\"Yazan:\" \/>\n\t<meta name=\"twitter:data1\" content=\"Fatih Soysal\" \/>\n\t<meta name=\"twitter:label2\" content=\"Tahmini okuma s\u00fcresi\" \/>\n\t<meta name=\"twitter:data2\" content=\"3 dakika\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":\"Article\",\"@id\":\"https:\/\/fatihsoysal.com\/blog\/r-ile-sinir-aglari-bastan-sona-kapsamli-bir-rehber\/#article\",\"isPartOf\":{\"@id\":\"https:\/\/fatihsoysal.com\/blog\/r-ile-sinir-aglari-bastan-sona-kapsamli-bir-rehber\/\"},\"author\":{\"name\":\"Fatih Soysal\",\"@id\":\"https:\/\/fatihsoysal.com\/blog\/#\/schema\/person\/002a254750921dcfd568a99e48240dd1\"},\"headline\":\"R ile Sinir A\u011flar\u0131: Ba\u015ftan Sona Kapsaml\u0131 Bir Rehber\",\"datePublished\":\"2025-08-24T11:30:27+00:00\",\"mainEntityOfPage\":{\"@id\":\"https:\/\/fatihsoysal.com\/blog\/r-ile-sinir-aglari-bastan-sona-kapsamli-bir-rehber\/\"},\"wordCount\":1911,\"commentCount\":0,\"publisher\":{\"@id\":\"https:\/\/fatihsoysal.com\/blog\/#\/schema\/person\/002a254750921dcfd568a99e48240dd1\"},\"inLanguage\":\"tr\",\"potentialAction\":[{\"@type\":\"CommentAction\",\"name\":\"Comment\",\"target\":[\"https:\/\/fatihsoysal.com\/blog\/r-ile-sinir-aglari-bastan-sona-kapsamli-bir-rehber\/#respond\"]}],\"copyrightYear\":\"2025\",\"copyrightHolder\":{\"@id\":\"https:\/\/fatihsoysal.com\/blog\/#organization\"}},{\"@type\":\"WebPage\",\"@id\":\"https:\/\/fatihsoysal.com\/blog\/r-ile-sinir-aglari-bastan-sona-kapsamli-bir-rehber\/\",\"url\":\"https:\/\/fatihsoysal.com\/blog\/r-ile-sinir-aglari-bastan-sona-kapsamli-bir-rehber\/\",\"name\":\"R ile Sinir A\u011flar\u0131: Ba\u015ftan Sona Kapsaml\u0131 Bir Rehber\",\"isPartOf\":{\"@id\":\"https:\/\/fatihsoysal.com\/blog\/#website\"},\"datePublished\":\"2025-08-24T11:30:27+00:00\",\"description\":\"Karma\u015f\u0131k veri k\u00fcmelerinden anlaml\u0131 i\u00e7g\u00f6r\u00fcler \u00e7\u0131karmak, g\u00fcn\u00fcm\u00fcz d\u00fcnyas\u0131nda hayati \u00f6nem ta\u015f\u0131yor. Bu i\u00e7g\u00f6r\u00fcleri elde etmek i\u00e7in g\u00fc\u00e7l\u00fc bir ara\u00e7 olan sinir a\u011flar\u0131, R programlama diliyle birle\u015fti\u011finde, veri analizi ve makine \u00f6\u011frenmesinde devrim yarat\u0131yor. Bu rehber, R kullanarak sinir a\u011flar\u0131n\u0131 s\u0131f\u0131rdan ileri seviyeye kadar ad\u0131m ad\u0131m \u00f6\u011frenmenizi sa\u011flayacak, ger\u00e7ek d\u00fcnya \u00f6rnekleriyle zenginle\u015ftirilmi\u015f kapsaml\u0131 bir yolculu\u011fa \u00e7\u0131kar\u0131yor.\",\"breadcrumb\":{\"@id\":\"https:\/\/fatihsoysal.com\/blog\/r-ile-sinir-aglari-bastan-sona-kapsamli-bir-rehber\/#breadcrumb\"},\"inLanguage\":\"tr\",\"potentialAction\":[{\"@type\":\"ReadAction\",\"target\":[\"https:\/\/fatihsoysal.com\/blog\/r-ile-sinir-aglari-bastan-sona-kapsamli-bir-rehber\/\"]}]},{\"@type\":\"BreadcrumbList\",\"@id\":\"https:\/\/fatihsoysal.com\/blog\/r-ile-sinir-aglari-bastan-sona-kapsamli-bir-rehber\/#breadcrumb\",\"itemListElement\":[{\"@type\":\"ListItem\",\"position\":1,\"name\":\"Anasayfa\",\"item\":\"https:\/\/fatihsoysal.com\/blog\/\"},{\"@type\":\"ListItem\",\"position\":2,\"name\":\"R ile Sinir A\u011flar\u0131: Ba\u015ftan Sona Kapsaml\u0131 Bir Rehber\"}]},{\"@type\":\"WebSite\",\"@id\":\"https:\/\/fatihsoysal.com\/blog\/#website\",\"url\":\"https:\/\/fatihsoysal.com\/blog\/\",\"name\":\"Fatihsoysal.com\",\"description\":\"Blog - Yaz\u0131l\u0131m D\u00fcnyas\u0131 Tecr\u00fcbelerim\",\"publisher\":{\"@id\":\"https:\/\/fatihsoysal.com\/blog\/#\/schema\/person\/002a254750921dcfd568a99e48240dd1\"},\"potentialAction\":[{\"@type\":\"SearchAction\",\"target\":{\"@type\":\"EntryPoint\",\"urlTemplate\":\"https:\/\/fatihsoysal.com\/blog\/?s={search_term_string}\"},\"query-input\":{\"@type\":\"PropertyValueSpecification\",\"valueRequired\":true,\"valueName\":\"search_term_string\"}}],\"inLanguage\":\"tr\"},{\"@type\":[\"Person\",\"Organization\"],\"@id\":\"https:\/\/fatihsoysal.com\/blog\/#\/schema\/person\/002a254750921dcfd568a99e48240dd1\",\"name\":\"Fatih Soysal\",\"image\":{\"@type\":\"ImageObject\",\"inLanguage\":\"tr\",\"@id\":\"https:\/\/fatihsoysal.com\/blog\/#\/schema\/person\/image\/\",\"url\":\"https:\/\/fatihsoysal.com\/blog\/wp-content\/uploads\/2024\/04\/cropped-replicate-prediction-3kgg1hgjn5rgp0cf0p5tr0jw7w-1.png\",\"contentUrl\":\"https:\/\/fatihsoysal.com\/blog\/wp-content\/uploads\/2024\/04\/cropped-replicate-prediction-3kgg1hgjn5rgp0cf0p5tr0jw7w-1.png\",\"width\":512,\"height\":512,\"caption\":\"Fatih Soysal\"},\"logo\":{\"@id\":\"https:\/\/fatihsoysal.com\/blog\/#\/schema\/person\/image\/\"},\"description\":\"Kullan\u0131m ve kodlama m\u00fckemmeliyetini odak alan uygulamalar olu\u015fturma deneyimine sahip, profesyonel olarak 15+ y\u0131l \u00fczeri deneyime sahip bir yaz\u0131l\u0131m m\u00fchendisi.\",\"url\":\"https:\/\/fatihsoysal.com\/blog\/author\/fatihsoysal\/\"}]}<\/script>\n<!-- \/ Yoast SEO Premium plugin. -->","yoast_head_json":{"title":"R ile Sinir A\u011flar\u0131: Ba\u015ftan Sona Kapsaml\u0131 Bir Rehber","description":"Karma\u015f\u0131k veri k\u00fcmelerinden anlaml\u0131 i\u00e7g\u00f6r\u00fcler \u00e7\u0131karmak, g\u00fcn\u00fcm\u00fcz d\u00fcnyas\u0131nda hayati \u00f6nem ta\u015f\u0131yor. Bu i\u00e7g\u00f6r\u00fcleri elde etmek i\u00e7in g\u00fc\u00e7l\u00fc bir ara\u00e7 olan sinir a\u011flar\u0131, R programlama diliyle birle\u015fti\u011finde, veri analizi ve makine \u00f6\u011frenmesinde devrim yarat\u0131yor. Bu rehber, R kullanarak sinir a\u011flar\u0131n\u0131 s\u0131f\u0131rdan ileri seviyeye kadar ad\u0131m ad\u0131m \u00f6\u011frenmenizi sa\u011flayacak, ger\u00e7ek d\u00fcnya \u00f6rnekleriyle zenginle\u015ftirilmi\u015f kapsaml\u0131 bir yolculu\u011fa \u00e7\u0131kar\u0131yor.","robots":{"index":"index","follow":"follow","max-snippet":"max-snippet:-1","max-image-preview":"max-image-preview:large","max-video-preview":"max-video-preview:-1"},"canonical":"https:\/\/fatihsoysal.com\/blog\/r-ile-sinir-aglari-bastan-sona-kapsamli-bir-rehber\/","og_locale":"tr_TR","og_type":"article","og_title":"R ile Sinir A\u011flar\u0131: Ba\u015ftan Sona Kapsaml\u0131 Bir Rehber","og_description":"Karma\u015f\u0131k veri k\u00fcmelerinden anlaml\u0131 i\u00e7g\u00f6r\u00fcler \u00e7\u0131karmak, g\u00fcn\u00fcm\u00fcz d\u00fcnyas\u0131nda hayati \u00f6nem ta\u015f\u0131yor. Bu i\u00e7g\u00f6r\u00fcleri elde etmek i\u00e7in g\u00fc\u00e7l\u00fc bir ara\u00e7 olan sinir a\u011flar\u0131, R programlama diliyle birle\u015fti\u011finde, veri analizi ve makine \u00f6\u011frenmesinde devrim yarat\u0131yor. Bu rehber, R kullanarak sinir a\u011flar\u0131n\u0131 s\u0131f\u0131rdan ileri seviyeye kadar ad\u0131m ad\u0131m \u00f6\u011frenmenizi sa\u011flayacak, ger\u00e7ek d\u00fcnya \u00f6rnekleriyle zenginle\u015ftirilmi\u015f kapsaml\u0131 bir yolculu\u011fa \u00e7\u0131kar\u0131yor.","og_url":"https:\/\/fatihsoysal.com\/blog\/r-ile-sinir-aglari-bastan-sona-kapsamli-bir-rehber\/","og_site_name":"Kodlar\u0131n Gizemli D\u00fcnyas\u0131","article_published_time":"2025-08-24T11:30:27+00:00","author":"Fatih Soysal","twitter_card":"summary_large_image","twitter_misc":{"Yazan:":"Fatih Soysal","Tahmini okuma s\u00fcresi":"3 dakika"},"schema":{"@context":"https:\/\/schema.org","@graph":[{"@type":"Article","@id":"https:\/\/fatihsoysal.com\/blog\/r-ile-sinir-aglari-bastan-sona-kapsamli-bir-rehber\/#article","isPartOf":{"@id":"https:\/\/fatihsoysal.com\/blog\/r-ile-sinir-aglari-bastan-sona-kapsamli-bir-rehber\/"},"author":{"name":"Fatih Soysal","@id":"https:\/\/fatihsoysal.com\/blog\/#\/schema\/person\/002a254750921dcfd568a99e48240dd1"},"headline":"R ile Sinir A\u011flar\u0131: Ba\u015ftan Sona Kapsaml\u0131 Bir Rehber","datePublished":"2025-08-24T11:30:27+00:00","mainEntityOfPage":{"@id":"https:\/\/fatihsoysal.com\/blog\/r-ile-sinir-aglari-bastan-sona-kapsamli-bir-rehber\/"},"wordCount":1911,"commentCount":0,"publisher":{"@id":"https:\/\/fatihsoysal.com\/blog\/#\/schema\/person\/002a254750921dcfd568a99e48240dd1"},"inLanguage":"tr","potentialAction":[{"@type":"CommentAction","name":"Comment","target":["https:\/\/fatihsoysal.com\/blog\/r-ile-sinir-aglari-bastan-sona-kapsamli-bir-rehber\/#respond"]}],"copyrightYear":"2025","copyrightHolder":{"@id":"https:\/\/fatihsoysal.com\/blog\/#organization"}},{"@type":"WebPage","@id":"https:\/\/fatihsoysal.com\/blog\/r-ile-sinir-aglari-bastan-sona-kapsamli-bir-rehber\/","url":"https:\/\/fatihsoysal.com\/blog\/r-ile-sinir-aglari-bastan-sona-kapsamli-bir-rehber\/","name":"R ile Sinir A\u011flar\u0131: Ba\u015ftan Sona Kapsaml\u0131 Bir Rehber","isPartOf":{"@id":"https:\/\/fatihsoysal.com\/blog\/#website"},"datePublished":"2025-08-24T11:30:27+00:00","description":"Karma\u015f\u0131k veri k\u00fcmelerinden anlaml\u0131 i\u00e7g\u00f6r\u00fcler \u00e7\u0131karmak, g\u00fcn\u00fcm\u00fcz d\u00fcnyas\u0131nda hayati \u00f6nem ta\u015f\u0131yor. Bu i\u00e7g\u00f6r\u00fcleri elde etmek i\u00e7in g\u00fc\u00e7l\u00fc bir ara\u00e7 olan sinir a\u011flar\u0131, R programlama diliyle birle\u015fti\u011finde, veri analizi ve makine \u00f6\u011frenmesinde devrim yarat\u0131yor. Bu rehber, R kullanarak sinir a\u011flar\u0131n\u0131 s\u0131f\u0131rdan ileri seviyeye kadar ad\u0131m ad\u0131m \u00f6\u011frenmenizi sa\u011flayacak, ger\u00e7ek d\u00fcnya \u00f6rnekleriyle zenginle\u015ftirilmi\u015f kapsaml\u0131 bir yolculu\u011fa \u00e7\u0131kar\u0131yor.","breadcrumb":{"@id":"https:\/\/fatihsoysal.com\/blog\/r-ile-sinir-aglari-bastan-sona-kapsamli-bir-rehber\/#breadcrumb"},"inLanguage":"tr","potentialAction":[{"@type":"ReadAction","target":["https:\/\/fatihsoysal.com\/blog\/r-ile-sinir-aglari-bastan-sona-kapsamli-bir-rehber\/"]}]},{"@type":"BreadcrumbList","@id":"https:\/\/fatihsoysal.com\/blog\/r-ile-sinir-aglari-bastan-sona-kapsamli-bir-rehber\/#breadcrumb","itemListElement":[{"@type":"ListItem","position":1,"name":"Anasayfa","item":"https:\/\/fatihsoysal.com\/blog\/"},{"@type":"ListItem","position":2,"name":"R ile Sinir A\u011flar\u0131: Ba\u015ftan Sona Kapsaml\u0131 Bir Rehber"}]},{"@type":"WebSite","@id":"https:\/\/fatihsoysal.com\/blog\/#website","url":"https:\/\/fatihsoysal.com\/blog\/","name":"Fatihsoysal.com","description":"Blog - Yaz\u0131l\u0131m D\u00fcnyas\u0131 Tecr\u00fcbelerim","publisher":{"@id":"https:\/\/fatihsoysal.com\/blog\/#\/schema\/person\/002a254750921dcfd568a99e48240dd1"},"potentialAction":[{"@type":"SearchAction","target":{"@type":"EntryPoint","urlTemplate":"https:\/\/fatihsoysal.com\/blog\/?s={search_term_string}"},"query-input":{"@type":"PropertyValueSpecification","valueRequired":true,"valueName":"search_term_string"}}],"inLanguage":"tr"},{"@type":["Person","Organization"],"@id":"https:\/\/fatihsoysal.com\/blog\/#\/schema\/person\/002a254750921dcfd568a99e48240dd1","name":"Fatih Soysal","image":{"@type":"ImageObject","inLanguage":"tr","@id":"https:\/\/fatihsoysal.com\/blog\/#\/schema\/person\/image\/","url":"https:\/\/fatihsoysal.com\/blog\/wp-content\/uploads\/2024\/04\/cropped-replicate-prediction-3kgg1hgjn5rgp0cf0p5tr0jw7w-1.png","contentUrl":"https:\/\/fatihsoysal.com\/blog\/wp-content\/uploads\/2024\/04\/cropped-replicate-prediction-3kgg1hgjn5rgp0cf0p5tr0jw7w-1.png","width":512,"height":512,"caption":"Fatih Soysal"},"logo":{"@id":"https:\/\/fatihsoysal.com\/blog\/#\/schema\/person\/image\/"},"description":"Kullan\u0131m ve kodlama m\u00fckemmeliyetini odak alan uygulamalar olu\u015fturma deneyimine sahip, profesyonel olarak 15+ y\u0131l \u00fczeri deneyime sahip bir yaz\u0131l\u0131m m\u00fchendisi.","url":"https:\/\/fatihsoysal.com\/blog\/author\/fatihsoysal\/"}]}},"yoast_meta":{"yoast_wpseo_title":"","yoast_wpseo_metadesc":"","yoast_wpseo_canonical":""},"amp_enabled":true,"_links":{"self":[{"href":"https:\/\/fatihsoysal.com\/blog\/wp-json\/wp\/v2\/posts\/28183","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/fatihsoysal.com\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/fatihsoysal.com\/blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/fatihsoysal.com\/blog\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/fatihsoysal.com\/blog\/wp-json\/wp\/v2\/comments?post=28183"}],"version-history":[{"count":0,"href":"https:\/\/fatihsoysal.com\/blog\/wp-json\/wp\/v2\/posts\/28183\/revisions"}],"wp:attachment":[{"href":"https:\/\/fatihsoysal.com\/blog\/wp-json\/wp\/v2\/media?parent=28183"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/fatihsoysal.com\/blog\/wp-json\/wp\/v2\/categories?post=28183"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/fatihsoysal.com\/blog\/wp-json\/wp\/v2\/tags?post=28183"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}