{"id":29396,"date":"2025-09-12T14:00:34","date_gmt":"2025-09-12T11:00:34","guid":{"rendered":"https:\/\/fatihsoysal.com\/blog\/edgebert-kendi-sinir-agi-cikarim-motorumu-rust-ile-nasil-olusturdum\/"},"modified":"2025-09-12T14:00:34","modified_gmt":"2025-09-12T11:00:34","slug":"edgebert-kendi-sinir-agi-cikarim-motorumu-rust-ile-nasil-olusturdum","status":"publish","type":"post","link":"https:\/\/fatihsoysal.com\/blog\/edgebert-kendi-sinir-agi-cikarim-motorumu-rust-ile-nasil-olusturdum\/","title":{"rendered":"EdgeBERT: Kendi Sinir A\u011f\u0131 \u00c7\u0131kar\u0131m Motorumu Rust ile Nas\u0131l Olu\u015fturdum?"},"content":{"rendered":"

EdgeBERT: Kendi Sinir A\u011f\u0131 \u00c7\u0131kar\u0131m Motorumu Rust ile Nas\u0131l Olu\u015fturdum?<\/p>\n

Yapay zeka uygulamalar\u0131n\u0131n h\u0131zla geli\u015fmesiyle birlikte, yapay zeka modellerinin ger\u00e7ek zamanl\u0131 olarak \u00e7al\u0131\u015ft\u0131r\u0131lmas\u0131 b\u00fcy\u00fck \u00f6nem kazanm\u0131\u015ft\u0131r. Bu ihtiyac\u0131 kar\u015f\u0131lamak i\u00e7in geli\u015ftirilen EdgeBERT, Rust programlama diliyle yaz\u0131lm\u0131\u015f, performans odakl\u0131 bir sinir a\u011f\u0131 \u00e7\u0131kar\u0131m motorudur. Bu makale, EdgeBERT’in geli\u015ftirilme s\u00fcrecini, temel kavramlar\u0131n\u0131, uygulamal\u0131 \u00f6rneklerini ve ileri d\u00fczey kullan\u0131m\u0131n\u0131 ad\u0131m ad\u0131m a\u00e7\u0131klayacakt\u0131r. Rust’\u0131n performans avantajlar\u0131ndan ve EdgeBERT’in sundu\u011fu \u00e7\u00f6z\u00fcmlerden yararlanarak, kendi yapay zeka uygulamalar\u0131n\u0131z\u0131 geli\u015ftirmek i\u00e7in gerekli ad\u0131mlar\u0131 \u00f6\u011freneceksiniz. EdgeBERT ile, d\u00fc\u015f\u00fck gecikmeli ve y\u00fcksek performansl\u0131 yapay zeka uygulamalar\u0131 geli\u015ftirebilirsiniz.<\/p>\n

EdgeBERT: Neden Rust? Performans Odakl\u0131 Yapay Zeka \u00c7\u0131kar\u0131m\u0131 \u0130\u00e7in Bir Bak\u0131\u015f<\/h2>\n

Rust, bellek g\u00fcvenli\u011fi ve performans\u0131yla bilinen bir sistem programlama dilidir. Bellek y\u00f6netimi konusundaki titiz yap\u0131s\u0131, bellek s\u0131z\u0131nt\u0131lar\u0131n\u0131 ve bellek bozulmalar\u0131n\u0131 \u00f6nleyerek, \u00f6zellikle g\u00f6m\u00fcl\u00fc sistemler ve performans kritik uygulamalar i\u00e7in ideal bir tercihtir. Bu \u00f6zelli\u011fi, EdgeBERT gibi ger\u00e7ek zamanl\u0131 sinir a\u011f\u0131 \u00e7\u0131kar\u0131m motorlar\u0131 i\u00e7in \u00e7ok \u00f6nemlidir. Rust’\u0131n, C++’a g\u00f6re daha modern ve daha okunabilir bir s\u00f6zdizimine sahip olmas\u0131, geli\u015ftirme s\u00fcrecini h\u0131zland\u0131r\u0131r ve kodun bak\u0131m\u0131 kolayla\u015ft\u0131r\u0131r. Ayr\u0131ca, Rust’\u0131n geni\u015fleyen ekosistemi, \u00e7e\u015fitli k\u00fct\u00fcphaneler ve ara\u00e7lar sunarak EdgeBERT’in geli\u015ftirilmesini destekler. \u00d6rne\u011fin, Rust’\u0131n vekt\u00f6rle\u015fme yetenekleri ve paralel i\u015flem deste\u011fi, sinir a\u011f\u0131 hesaplamalar\u0131n\u0131n h\u0131zland\u0131r\u0131lmas\u0131na yard\u0131mc\u0131 olur. Bu nedenle, EdgeBERT’in Rust ile yaz\u0131lmas\u0131, hem performans hem de g\u00fcvenilirlik a\u00e7\u0131s\u0131ndan b\u00fcy\u00fck avantajlar sa\u011flar. Bu, EdgeBERT’i mobil cihazlardan IoT cihazlar\u0131na kadar geni\u015f bir yelpazede kullan\u0131labilen esnek bir \u00e7\u00f6z\u00fcm yapar. Di\u011fer dillerle k\u0131yasland\u0131\u011f\u0131nda, Rust’\u0131n performans avantajlar\u0131 g\u00f6z ard\u0131 edilemez. \u00d6zellikle, geleneksel Python tabanl\u0131 \u00e7\u00f6z\u00fcmlere g\u00f6re \u00f6nemli bir performans art\u0131\u015f\u0131 sunar.<\/p>\n

EdgeBERT’i Anlamak: Temel Kavramlar<\/h2>\n

EdgeBERT, temelde bir sinir a\u011f\u0131 modelini y\u00fckleyip, verileri i\u015fleyerek tahminler \u00fcreten bir motordur. Bu s\u00fcre\u00e7, birka\u00e7 temel a\u015famadan olu\u015fur:<\/p>\n

1. Model Y\u00fcklenmesi:<\/strong> EdgeBERT, \u00e7e\u015fitli sinir a\u011f\u0131 \u00e7er\u00e7eveleri (\u00f6rne\u011fin, TensorFlow Lite, ONNX) taraf\u0131ndan olu\u015fturulmu\u015f modelleri destekler. Model, ilk olarak belle\u011fe y\u00fcklenir ve uygun bir formata d\u00f6n\u00fc\u015ft\u00fcr\u00fcl\u00fcr.<\/p>\n

2. Veri \u00d6n \u0130\u015fleme:<\/strong> Giri\u015f verileri, modelin beklentilerine uygun olarak i\u015flenir. Bu, verilerin boyutland\u0131r\u0131lmas\u0131, normalize edilmesi ve d\u00f6n\u00fc\u015ft\u00fcr\u00fclmesini i\u00e7erir.<\/p>\n

3. \u00c7\u0131kar\u0131m:<\/strong> Y\u00fcklenmi\u015f model, \u00f6n i\u015flenmi\u015f veriler \u00fczerinde \u00e7al\u0131\u015ft\u0131r\u0131larak tahminler \u00fcretilir. Bu ad\u0131m, modelin mimarisine ve karma\u015f\u0131kl\u0131\u011f\u0131na ba\u011fl\u0131 olarak \u00f6nemli miktarda hesaplama gerektirir.<\/p>\n

4. Sonu\u00e7 \u0130\u015fleme:<\/strong> Modelin \u00fcretti\u011fi ham \u00e7\u0131kt\u0131lar, anlaml\u0131 sonu\u00e7lar elde etmek i\u00e7in i\u015flenir. \u00d6rne\u011fin, bir s\u0131n\u0131fland\u0131rma probleminde, en y\u00fcksek olas\u0131l\u0131kl\u0131 s\u0131n\u0131f se\u00e7ilir.<\/p>\n

EdgeBERT, bu ad\u0131mlar\u0131 optimize edilmi\u015f algoritmalar ve verimli veri yap\u0131lar\u0131 kullanarak ger\u00e7ekle\u015ftirir. Rust’\u0131n performans odakl\u0131 yap\u0131s\u0131, bu optimizasyonlar\u0131 uygulamay\u0131 kolayla\u015ft\u0131r\u0131r. Ayr\u0131ca, EdgeBERT, farkl\u0131 i\u015flemcilere ve donan\u0131mlara uyum sa\u011flayacak \u015fekilde tasarlanm\u0131\u015ft\u0131r. Bu, EdgeBERT’i \u00e7e\u015fitli cihazlarda \u00e7al\u0131\u015ft\u0131rabilmenizi sa\u011flar.<\/p>\n

EdgeBERT’i Uygulamak: Ad\u0131m Ad\u0131m Bir \u00d6rnek<\/h2>\n

Bu b\u00f6l\u00fcmde, basit bir g\u00f6r\u00fcnt\u00fc s\u0131n\u0131fland\u0131rma \u00f6rne\u011fi \u00fczerinden EdgeBERT’in nas\u0131l kullan\u0131laca\u011f\u0131n\u0131 g\u00f6sterece\u011fiz. A\u015fa\u011f\u0131daki ad\u0131mlar\u0131 takip edebilirsiniz:<\/p>\n

1. Gereksinimleri Kurun:<\/strong> \u0130lk olarak, Rust ve gerekli k\u00fct\u00fcphaneleri kurman\u0131z gerekir.<\/p>\n

cargo install edgebert<\/pre>\n
<\/code><\/p>\n
2. Bir Model Y\u00fckleyin:<\/strong>  EdgeBERT, \u00f6nceden e\u011fitilmi\u015f modellerle \u00e7al\u0131\u015f\u0131r.  Bir model indirmeniz ve EdgeBERT'in anlayabilece\u011fi bir formata d\u00f6n\u00fc\u015ft\u00fcrmeniz gerekir. \u00d6rne\u011fin,  TensorFlow Lite modeli kullanabilirsiniz.\n\n3. Kodu Yaz\u0131n:<\/strong>  A\u015fa\u011f\u0131daki Rust kodu, bir g\u00f6r\u00fcnt\u00fcy\u00fc y\u00fckleyip, EdgeBERT kullanarak s\u0131n\u0131fland\u0131r\u0131r:<\/pre>\n
<\/code>use edgebert::EdgeBERT;<\/p>\n
fn main() -> Result<(), Box> {
\n    let mut edgebert = EdgeBERT::new(\"model.tflite\")?; \/\/ Model dosyan\u0131z\u0131n yolu
\n    let image = image::open(\"image.jpg\")?; \/\/ G\u00f6r\u00fcnt\u00fc dosyan\u0131z\u0131n yolu
\n    let prediction = edgebert.predict(&image)?;
\n    println!(\"Prediction: {:?}\", prediction);
\n    Ok(())
\n}<\/code><\/p>\n
4. \u00c7al\u0131\u015ft\u0131r\u0131n:<\/strong>  Kodu derleyip \u00e7al\u0131\u015ft\u0131r\u0131n.  Sonu\u00e7 olarak, g\u00f6r\u00fcnt\u00fcn\u00fcn s\u0131n\u0131fland\u0131r\u0131lmas\u0131n\u0131 g\u00f6receksiniz.<\/p>\n
Bu basit \u00f6rnek, EdgeBERT'in temel kullan\u0131m\u0131n\u0131 g\u00f6sterir.  Daha karma\u015f\u0131k uygulamalar i\u00e7in,  EdgeBERT'in dok\u00fcmantasyonuna bakabilirsiniz.  Daha fazla bilgi i\u00e7in fatihsoysal.com adresini ziyaret edebilirsiniz.<\/a><\/p>\n
EdgeBERT Performans Optimizasyonu: \u0130leri D\u00fczey Teknikler<\/h2>\n
EdgeBERT'in performans\u0131n\u0131 daha da iyile\u015ftirmek i\u00e7in \u00e7e\u015fitli ileri d\u00fczey teknikler kullan\u0131labilir.  Bunlardan baz\u0131lar\u0131:<\/p>\n
* Vekt\u00f6rle\u015ftirme:<\/strong>  Rust'\u0131n SIMD (Single Instruction, Multiple Data) yeteneklerini kullanarak,  birden fazla veri \u00f6\u011fesini ayn\u0131 anda i\u015fleyebilirsiniz.  Bu,  hesaplama h\u0131z\u0131n\u0131 \u00f6nemli \u00f6l\u00e7\u00fcde art\u0131r\u0131r.<\/p>\n
* Paralel \u0130\u015flem:<\/strong>  \u00c7ok \u00e7ekirdekli i\u015flemcilerden yararlanarak,  i\u015f y\u00fck\u00fcn\u00fc farkl\u0131 \u00e7ekirdeklere da\u011f\u0131tabilirsiniz.  Rust'\u0131n paralel programlama k\u00fct\u00fcphaneleri,  bu i\u015flemi kolayla\u015ft\u0131r\u0131r.<\/p>\n
* Bellek Optimizasyonu:<\/strong>  Veri yap\u0131lar\u0131n\u0131 ve bellek eri\u015fim kal\u0131plar\u0131n\u0131 optimize ederek,  bellek bant geni\u015fli\u011fi kullan\u0131m\u0131n\u0131 art\u0131rabilirsiniz.<\/p>\n
* GPU H\u0131zland\u0131rmas\u0131:<\/strong>  E\u011fer m\u00fcmk\u00fcnse,  GPU'yu kullanarak hesaplamalar\u0131 h\u0131zland\u0131rabilirsiniz.  Rust'\u0131n \u00e7e\u015fitli GPU programlama k\u00fct\u00fcphaneleriyle entegre edilebilir.<\/p>\n
Bu teknikleri kullanarak, EdgeBERT'in performans\u0131n\u0131 \u00f6nemli \u00f6l\u00e7\u00fcde art\u0131rabilirsiniz.  Ancak,  bu optimizasyonlar\u0131n uygulama maliyeti de g\u00f6z \u00f6n\u00fcnde bulundurulmal\u0131d\u0131r.<\/p>\n
Ger\u00e7ek D\u00fcnya Senaryolar\u0131: EdgeBERT Uygulama \u00d6rnekleri<\/h2>\n
EdgeBERT, \u00e7e\u015fitli ger\u00e7ek d\u00fcnya senaryolar\u0131nda kullan\u0131labilir.  \u0130\u015fte baz\u0131 \u00f6rnekler:<\/p>\n
* Nesne Alg\u0131lama:<\/strong>  G\u00fcvenlik kameralar\u0131nda nesne alg\u0131lama yapmak i\u00e7in kullan\u0131labilir.  Ger\u00e7ek zamanl\u0131 olarak tehlikeli durumlar\u0131 tespit edebilir.<\/p>\n
* G\u00f6r\u00fcnt\u00fc S\u0131n\u0131fland\u0131rma:<\/strong>  T\u0131pta hastal\u0131k te\u015fhisi veya tar\u0131mda \u00fcr\u00fcn s\u0131n\u0131fland\u0131rmas\u0131 gibi uygulamalarda kullan\u0131labilir.<\/p>\n
* Konu\u015fma Tan\u0131ma:<\/strong>  Sesli asistanlar ve konu\u015fma tabanl\u0131 aray\u00fczler i\u00e7in kullan\u0131labilir.  Ger\u00e7ek zamanl\u0131 olarak konu\u015fmay\u0131 anlayabilir.<\/p>\n
* Duygu Analizi:<\/strong>  Sosyal medya duygu analizinde kullan\u0131labilir.  Yorumlar\u0131 ve g\u00f6nderileri analiz ederek genel duyguyu belirleyebilir.<\/p>\n
EdgeBERT G\u00fcvenlik ve Hata Y\u00f6netimi<\/h2>\n
EdgeBERT'i kullan\u0131rken, g\u00fcvenlik ve hata y\u00f6netimi \u00f6nemlidir.  Modelin g\u00fcvenilirli\u011fini ve do\u011frulu\u011funu sa\u011flamak i\u00e7in, a\u015fa\u011f\u0131daki noktalara dikkat edilmelidir:<\/p>\n
\n  Dikkat:<\/strong>  Modelin e\u011fitimi ve verileri, g\u00fcvenlik a\u00e7\u0131s\u0131ndan \u00f6nemlidir.  Yanl\u0131\u015f e\u011fitilmi\u015f veya \u00f6nyarg\u0131l\u0131 bir model, yanl\u0131\u015f sonu\u00e7lara yol a\u00e7abilir.\n<\/div>\n
Hata y\u00f6netimi i\u00e7in, EdgeBERT, \u00e7e\u015fitli hata durumlar\u0131n\u0131 ele al\u0131r ve bunlar\u0131 kullan\u0131c\u0131ya bildirir.  Uygulama,  olas\u0131 hatalar\u0131 yakalamak ve uygun \u015fekilde ele almak i\u00e7in tasarlanm\u0131\u015ft\u0131r.  Ayr\u0131ca,  uygulaman\u0131zda uygun hata ay\u0131klama mekanizmalar\u0131 kullanmal\u0131s\u0131n\u0131z.<\/p>\n
EdgeBERT'in Gelece\u011fi ve \u00d6nemli Geli\u015fmeler<\/h2>\n
EdgeBERT, s\u00fcrekli olarak geli\u015ftirilmekte ve yeni \u00f6zellikler eklenmektedir.  Gelecekte,  daha fazla model deste\u011fi,  daha geli\u015fmi\u015f optimizasyonlar ve yeni platform entegrasyonlar\u0131 beklenmektedir.  Bunlar aras\u0131nda,  mobil cihazlar i\u00e7in daha iyi optimizasyon ve \u00e7e\u015fitli g\u00f6m\u00fcl\u00fc sistemlerle uyumluluk yer almaktad\u0131r.  Ayr\u0131ca,  EdgeBERT'in  daha karma\u015f\u0131k sinir a\u011f\u0131 mimarilerini desteklemek i\u00e7in geli\u015ftirilmesi hedeflenmektedir.  Daha fazla geli\u015fme ve g\u00fcncellemeler i\u00e7in fatihsoysal.com sitesini takip edebilirsiniz.<\/a><\/p>\n
Sonu\u00e7 ve S\u0131k\u00e7a Sorulan Sorular<\/h2>\n
EdgeBERT, Rust'\u0131n g\u00fcc\u00fcnden yararlanarak performans odakl\u0131 bir sinir a\u011f\u0131 \u00e7\u0131kar\u0131m motoru sunmaktad\u0131r.  Bu makalede, EdgeBERT'in temel kavramlar\u0131n\u0131, uygulamal\u0131 \u00f6rneklerini ve ileri d\u00fczey kullan\u0131m\u0131n\u0131 ele ald\u0131k.  Ger\u00e7ek d\u00fcnya senaryolar\u0131 ve performans optimizasyonlar\u0131 hakk\u0131nda bilgiler verdik.  EdgeBERT'in gelece\u011fi ve s\u00fcrekli geli\u015fimi,  yapay zeka uygulamalar\u0131n\u0131n daha da yayg\u0131nla\u015fmas\u0131na ve geli\u015fmesine katk\u0131da bulunacakt\u0131r.<\/p>\n
S\u0131k\u00e7a Sorulan Sorular:<\/strong><\/p>\n
1. EdgeBERT hangi i\u015fletim sistemlerinde \u00e7al\u0131\u015f\u0131r?<\/strong>  EdgeBERT, Linux, macOS ve Windows'da \u00e7al\u0131\u015fabilir.<\/p>\n
2. EdgeBERT hangi sinir a\u011f\u0131 \u00e7er\u00e7evelerini destekler?<\/strong>  \u015eu anda TensorFlow Lite ve ONNX desteklenmektedir.  Daha fazla \u00e7er\u00e7eve deste\u011fi gelecekte eklenecektir.<\/p>\n
3. EdgeBERT'in performans\u0131 nas\u0131l \u00f6l\u00e7\u00fcl\u00fcr?<\/strong>  Performans,  \u00e7\u0131kar\u0131m s\u00fcresi, bellek kullan\u0131m\u0131 ve enerji t\u00fcketimi gibi metriklerle \u00f6l\u00e7\u00fclebilir.<\/p>\n
4. EdgeBERT'i nas\u0131l \u00f6zelle\u015ftirebilirim?<\/strong>  EdgeBERT'in kaynak koduna eri\u015fiminiz varsa,  kodu de\u011fi\u015ftirerek \u00f6zelle\u015ftirebilirsiniz.<\/p>\n
5. EdgeBERT'in lisans\u0131 nedir?<\/strong>  EdgeBERT, a\u00e7\u0131k kaynakl\u0131 bir lisans alt\u0131nda da\u011f\u0131t\u0131lmaktad\u0131r.<\/p>\n
Yazar: Fatih Soysal<\/p>\n","protected":false},"excerpt":{"rendered":"EdgeBERT: Kendi Sinir A\u011f\u0131 \u00c7\u0131kar\u0131m Motorumu Rust ile Nas\u0131l Olu\u015fturdum? Yapay zeka uygulamalar\u0131n\u0131n h\u0131zla geli\u015fmesiyle birlikte, yapay zeka…","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-29396","1":"post","2":"type-post","3":"status-publish","4":"format-standard","6":"category-genel","7":"cs-entry","8":"cs-video-wrap"},"yoast_head":"\nEdgeBERT: Kendi Sinir A\u011f\u0131 \u00c7\u0131kar\u0131m Motorumu Rust ile Nas\u0131l Olu\u015fturdum?<\/title>\n<meta name=\"description\" content=\"Yapay zeka uygulamalar\u0131n\u0131n h\u0131zla geli\u015fmesiyle birlikte, yapay zeka modellerinin ger\u00e7ek zamanl\u0131 olarak \u00e7al\u0131\u015ft\u0131r\u0131lmas\u0131 b\u00fcy\u00fck \u00f6nem kazanm\u0131\u015ft\u0131r. Bu ihtiyac\u0131 kar\u015f\u0131lamak i\u00e7in geli\u015ftirilen EdgeBERT, Rust programlama diliyle yaz\u0131lm\u0131\u015f, performans odakl\u0131 bir sinir a\u011f\u0131 \u00e7\u0131kar\u0131m motorudur. Bu makale, EdgeBERT'in geli\u015ftirilme s\u00fcrecini, temel kavramlar\u0131n\u0131, uygulamal\u0131 \u00f6rneklerini ve ileri d\u00fczey kullan\u0131m\u0131n\u0131 ad\u0131m ad\u0131m a\u00e7\u0131klayacakt\u0131r. Rust'\u0131n performans avantajlar\u0131ndan ve EdgeBERT'in sundu\u011fu \u00e7\u00f6z\u00fcmlerden yararlanarak, kendi yapay zeka uygulamalar\u0131n\u0131z\u0131 geli\u015ftirmek i\u00e7in gerekli ad\u0131mlar\u0131 \u00f6\u011freneceksiniz. EdgeBERT ile, d\u00fc\u015f\u00fck gecikmeli ve y\u00fcksek performansl\u0131 yapay zeka uygulamalar\u0131 geli\u015ftirebilirsiniz.\" \/>\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\/edgebert-kendi-sinir-agi-cikarim-motorumu-rust-ile-nasil-olusturdum\/\" \/>\n<meta property=\"og:locale\" content=\"tr_TR\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"EdgeBERT: Kendi Sinir A\u011f\u0131 \u00c7\u0131kar\u0131m Motorumu Rust ile Nas\u0131l Olu\u015fturdum?\" \/>\n<meta property=\"og:description\" content=\"Yapay zeka uygulamalar\u0131n\u0131n h\u0131zla geli\u015fmesiyle birlikte, yapay zeka modellerinin ger\u00e7ek zamanl\u0131 olarak \u00e7al\u0131\u015ft\u0131r\u0131lmas\u0131 b\u00fcy\u00fck \u00f6nem kazanm\u0131\u015ft\u0131r. 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