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Item #:
222191968
PYTHON İLE MAKİNE ÖĞRENİMİ VE DERİN ÖĞRENME (Machine Learning & Deep Learning via Python)
Item #:
222191968
AUD 26
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What Stands Out
Comprehensive Coverage
Offers an extensive exploration of machine learning and deep learning concepts, catering to both beginners and advanced users while utilizing Python as the core programming language.
Hands-on Approach
Emphasizes practical learning through real-world projects and coding exercises, helping users apply theoretical knowledge effectively in various applications.
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Includes tips and strategies from industry experts, enhancing the learning experience with practical advice and best practices tailored for aspiring data scientists.
Product Details
- Python ile Makine Öğrenimi ve Derin Öğrenme kitabının başlangıcında Python ile program geliştirme sürecinin öğretilmesi anlatılmaktadır. Ardından yapay zeka ve makine öğreniminin temel kavramları tanıtılarak gradyan iniş optimizasyon algoritması, doğrusal regresyon modeli, doğrusal sınıflandırma modeli ve algılayıcı modeli gibi en temel makine öğrenimi modelleri ilginç uygulama örnekleriyle açıklanmaktadır. Sonrasında, sinir ağı modeli ve ilgili eğitim algoritmalarına tanıtılmaktadır. Okuyucuların sinir ağı modelini hızlı bir şekilde tanıyabilmeleri için önce algılayıcı sinir ağı modeli kolay anlaşılır bir dille anlatılmakta, ardından sinir ağı modelinin temel bileşenleri bir araya getirilerek kapsamlı bir açıklama sunulmaktadır. Kitap, kod yazma sürecinden başlayarak sinir ağı modellerinin eğitim adımları ve eğitim algoritmalarını derinlemesine incelemekte ve hiperparametre ayarlama, model testi gibi temel teknikleri mizahi bir dille analiz ederek sunmaktadır. Yeni başlayanlar için sağlam bir derin öğrenme temeli oluşturmayı hedefleyen kitap, aşırı uyum sorunu ve düzenlileştirme stratejilerinin yanı sıra aktivasyon fonksiyonlarının tasarım fikirlerine de odaklanmakta; programlama temelli bir yaklaşımla derin öğrenmenin temel ilkelerini ve modellerini anlaşılır bir şekilde tanıtmaktadır. Daha fazla göster
| Yayıncı | Nobel Akademik Yayıncılık |
| Yayınlanma Tarihi | 13 Şubat 2025 |
| Baskı | 1. |
| Dil | Türkçe |
| Baskı Uzunluğu | 330 sayfa |
| ISBN-10 | 6253860011 |
| ISBN-13 | 978-6253860011 |
| Boyutlar | 4 x 19 x 27 cm |
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Ali Şir Attila Format: Kağıt Kapak Editorial Review
PYTHON İLE MAKİNE ÖĞRENİMİ VE DERİN ÖĞRENME (Machine Learning & Deep Learning via Python) is a comprehensive resource published by Nobel Akademik Yayıncılık, designed for Turkish-speaking audiences. Spanning 330 pages, this book serves as a rich guide for tackling the complexities of machine learning and deep learning using Python. With its detailed explanations and practical examples, readers will be well-equipped to navigate the intricacies of these advanced topics. The first edition, released on February 13, 2025, not only appeals to learners but also professionals looking to enhance their skills in a rapidly evolving field.
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Pros
- Comprehensive content on machine learning concepts
- Practical examples for better understanding
- Well-structured for Turkish-speaking readers
- Published by a reputable academic publisher
- Lengthy yet concise coverage of topics
Cons
- Only available in Turkish language
Platform Trust & Buyer Confidence
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Eddie
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“Purchased from Europe and arrived within 10 days. Very happy with the service”
30 August 2026 · via Trustpilot
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David
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“Order arrived quickly and as ordered. Recommend”
10 September 2026 · via Trustpilot
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02 October 2026 · via Trustpilot
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“3D Crystal Puzzles - Roses In A Vase (Black and Purple) Brilliant transaction! Thank you so much for your excellent service! Items are exactly as described, in great condition and package very well, quality and appearance are excellent and the price was amazing. Fast delivery too! Highly recommended!”
07 October 2026 · via Trustpilot
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AUD 26
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Features & Benefits
- Learn Python programming and machine learning basics.
- Understand essential machine learning models with real-world examples.
- Dive into neural networks and their components clearly explained.
- Explore training algorithms and hyperparameter tuning in depth.
- Addresses overfitting issues and regularization strategies humorously.
- Creates a strong foundation in deep learning principles for beginners.
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