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170012730
Makine Öğrenmesi: Teorik Yönleri ve Pyhton Uygulamaları İle Bir Yapay Zeka Ekolü
Item #:
170012730
NAD 344
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Learning the basic information in this book will enable people who want to develop applications with Deep Learning, a subfield of machine learning, to create an important infrastructure.
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What Stands Out
Comprehensive Insights
Offers extensive coverage of both theoretical aspects and practical applications of machine learning, ensuring readers grasp the full scope of the subject.
Python Focus
Integrates Python applications, providing readers with hands-on experience and real-world examples to enhance their understanding and skills in machine learning.
Educational Resource
Serves as an invaluable resource for students and educators alike, catering to both newcomers and individuals seeking to deepen their AI knowledge.
Product Details
| Yayu0131ncu0131 | Nobel Akademik Yayu0131ncu0131lu0131k |
| Yayu0131nlanma Tarihi | 4 Mart 2020 |
| Basku0131 | 3. |
| Dil | Tu00fcrku00e7e |
| Basku0131 Uzunluu011fu | 312 sayfa |
| ISBN-10 | 6050331766 |
| ISBN-13 | 978-6050331769 |
| Boyutlar | 15 x 2 x 21.5 cm |
Product Description
Makine Öğrenmesi: Teorik Yönleri ve Pyhton Uygulamaları İle Bir Yapay Zeka Ekolü
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Customer Questions & Answers
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Question:
Who is this book intended for?
Answer: It's designed for beginners starting in Machine Learning and those currently developing applications or preparing theses in related fields. -
Question:
What programming language is primarily used in this book?
Answer: The book primarily uses Python, along with libraries such as NumPy, Pandas, and Matplotlib. -
Question:
What topics are essential covered in this book?
Answer: It covers theoretical aspects of algorithms, data processing, and several application development processes in Machine Learning.
Sinan Uğuz Format: Kağıt Kapak Editorial Review
Makine Öğrenmesi: Teorik Yönleri ve Pyhton Uygulamaları İle Bir Yapay Zeka Ekolü offers a comprehensive exploration of machine learning from its theoretical foundations to practical applications in Python. Published by Nobel Akademik Yayıncılı, this 312-page book serves as an excellent resource for both students and professionals in the field. Its content is presented in Turkish, making it accessible to a broader audience. Readers have praised its clear explanations and structured approach, indicating its effectiveness for learning complex concepts. The book's dimensions make it easy to handle, adding to its practicality for study.
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Pros
- Thorough coverage of machine learning principles
- Includes practical Python applications
- Clear explanations for complex concepts
- Accessible for Turkish-speaking audiences
- Easy to handle due to compact size
Cons
- May not cover the latest advancements in AI
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Features & Benefits
- Comprehensive guide to Machine Learning and Deep Learning.
- Covers theoretical aspects vital for understanding algorithms.
- Practical applications developed using Python's rich libraries.
- Perfect for both beginners and those currently developing applications.
- Includes topics from linear algebra and statistics for foundational knowledge.
- Enhances the ability to understand deep learning architectures.
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