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Super Study Guide: Dönüştürücüler ve Büyük Dil Modelleri

Büyük dil modellerine dair ana kavramları ve pratik uygulamaları kapsayan, açık ve görsellerle desteklenmiş bir rehber. Projeler, mülakatlar ve kişisel öğrenme için idealdir.

This book is a translation into Turkish of Super Study Guide: Transformers & Large Language Models which was originally written in English

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Bu kitap; mülakatlar, projeler veya kendi meraklarını gidermek isteyen herkes için büyük dil modellerinin iç işleyişini anlamaya yönelik, özlü ve görselli bir rehberdir.

Kitap 5 bölüme ayrılmıştır:

  • Temeller: yapay sinir ağları ile eğitim ve değerlendirme süreçlerinde önemli olan derin öğrenme kavramlarına giriş
  • Sözcük temsilleri: bölütleme algoritmaları, yoğun sözcük temsilleri (word2vec) ve cümle temsilleri (RNN, LSTM, GRU)
  • Dönüştürücüler: öz-dikkat mekanizmasının ardındaki motivasyon, kodlayıcı- kod çözücü mimarisi ve BERT, GPT ve T5 gibi ilgili varyasyonlara dair ayrıntılı bir inceleme, hesaplamaları hızlandırmaya yönelik ipuçları ve püf noktaları
  • Büyük dil modelleri: dönüştürücü tabanlı modelleri ayarlamak için ana teknikler, örneğin komut mühendisliği (parametre açısından verimli), ince ayarlama ve tercih ayarlaması
  • Uygulamalar: duygu çıkarımı, makine çevirisi, bilgi erişim destekli üretim ve daha birçok yaygın kullanım alanları ve ortak sorunlar

Bu sayfa, (1) kitabın basılı sürümünü zaten satın almış olanlar için ve (2) farklı bölgelerdeki satın alma gücü farklarını dengelemek amacıyla %15’lik bir self-servis indirim sunmaktadır. İlginiz ve desteğiniz için çok teşekkür ederiz!

This book is a translation into Turkish of Super Study Guide: Transformers & Large Language Models which was originally written in English

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About the Authors

Afshine Amidi

Afshine Amidi is currently teaching the Transformers & Large Language Models workshop at Stanford and is also leading LLM efforts at Netflix. Previously, he worked on the Gemini team at Google and used NLP techniques to solve complex queries. Before that, he worked at Uber Eats to improve the quality of the search and recommendation systems. On the side, Afshine published a few papers at the intersection of deep learning and computational biology. He holds a Bachelor’s and a Master’s Degree from École Centrale Paris and a Master’s Degree from MIT.

Shervine Amidi

Shervine Amidi is currently teaching the Transformers & Large Language Models workshop at Stanford and is also working on the Gemini team at Google to leverage LLMs for action-based queries. Previously, he worked on applied machine learning problems for recommender systems at Uber Eats where he focused on representation learning to better surface dish recommendations. On the side, Shervine published a few papers at the intersection of deep learning and computational biology. He holds a Bachelor’s and a Master’s Degree from École Centrale Paris and a Master’s Degree from Stanford University.

Merve Ayyüce KIZRAK

I am the translator of the book Super Study Guide: Transformers and Large Language Models.

With 15+ years of expertise in AI, my journey began in 2009 as an Electronics and Communications Engineer. Over time, I've specialized in CV, AI governance, and AI safety. I hold a Ph.D. in Electronics and Communication Engineering from Yıldız Technical University, a Master's in Economincs, FinTech from Bahçeşehir University, and certifications in AI Strategy from UC Berkeley and ISO/IEC 42001 AI System Management Lead Auditing, which have strengthened my leadership in the AI field.

During my tenure in academia, I had the privilege of conducting research, teaching, and consulting for private-sector companies. My work involved developing and managing AI-driven digital transformation projects, significantly improving production lines, and guiding businesses in data-driven innovation.

Since 2019, I have been an AI Specialist at the Presidency of the Republic of Türkiye's Digital Transformation Office, pivotal in developing Türkiye's National AI Strategy. I lead the "Data Space for Public Sector" project, focused on secure data sharing and sovereignty. It was recently selected for the "Role of Government as a Data Provider for AI" initiative by Oxford Insights, GPAI, and CEIMIA. This initiative highlights Türkiye's contributions to global AI advancements, a testament to our collective efforts. I'm one of the expert contributors to the report "Ready, Set, AI: AI Readiness in Emerging Markets," presented at the 2025 Davos Summit and published by Economist Impact.

I actively contribute to national data policy, collaborating with international organizations like the OECD, G20, EU, NATO, and the UN. As a member of the OECD AI Governance and AI Index Working Groups, I represent Türkiye in global discussions on ethical AI design and policy, fostering connections and sharing our perspectives with the global AI community.

My passion for AI safety and alignment is deeply rooted in my commitment to ethical AI. I serve as a member of the AI Safety Fundamentals community and facilitate AI Governance courses. My online AI and machine learning courses have impacted over 50k students on platforms like Udemy. I regularly share open-source content, including articles, code, and lecture notes, to raise awareness about AI and data governance, always focusing on ethical, responsible AI development.

My work extends beyond my professional roles. I am deeply committed to fostering ethical, responsible AI development and inspiring future AI professionals. I mentor AI initiatives through NGOs and lead AI competition teams to success, including first-place finishes at TEKNOFEST.

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