PYTHON İLE MAKİNE ÖĞRENİMİ VE DERİN ÖĞRENME (Machine Learning & Deep Learning via Python)
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PYTHON İLE MAKİNE ÖĞRENİMİ VE DERİN ÖĞRENME (Machine Learning & Deep Learning via Python)
Bu kitap, yeni başlayanlar için sağlam bir derin öğrenme temeli oluşturmayı hedeflemektedir.
PYTHON İLE MAKİNE ÖĞRENİMİ VE DERİN ÖĞRENME (Machine Learning & Deep Learning via Python)
物品 #: 222191968

PYTHON İLE MAKİNE ÖĞRENİMİ VE DERİN ÖĞRENME (Machine Learning & Deep Learning via Python)

物品 #: 222191968

HKD 125

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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.
Expert Insights
Includes tips and strategies from industry experts, enhancing the learning experience with practical advice and best practices tailored for aspiring data scientists.

產品詳情

Shop PYTHON İLE MAKİNE ÖĞRENİMİ VE DERİN ÖĞRENME (Machine Learning & Deep Learning via Python) online at a best price in 香港. 6253860011
  • 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
YayıncıNobel Akademik Yayıncılık
Yayınlanma Tarihi13 Şubat 2025
Baskı1.
DilTürkçe
Baskı Uzunluğu330 sayfa
ISBN-106253860011
ISBN-13978-6253860011
Boyutlar4 x 19 x 27 cm

產品敘述

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  • 題: PYTHON İLE MAKİNE ÖĞRENİMİ VE DERİN ÖĞRENME (Machine 可以在 Hong Kong 在線購物嗎？

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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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優點

  • 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

缺點

  • Only available in Turkish language

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HKD 125

現在訂購，約可在下列時間收貨： 星期五, 十月 30

QTY:

庫存僅剩 1 件商品。
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PCI DSS compliant and ISO 27001:2022 certified, with encrypted payments and full buyer protection on every order.

Our Top Logistics Partners
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Fastest cross-border delivery

特色和優勢

  • 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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