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- Machine Learning Foundations, Volume 1: Super...
Machine Learning Foundations, Volume 1: Supervised Learning
UZS 1157301
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Machine Learning Foundations, Volume 1: Supervised Learning, offers a comprehensive and accessible roadmap to the core algorithms and concepts behind modern AI systems.
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Mahsulot tafsilotlari
| Publisher | Addison-Wesley Professional |
| Publication date | February 2, 2026 |
| Edition | 1st |
| Language | English |
| Print length | 880 pages |
| ISBN-10 | 0135337860 |
| ISBN-13 | 978-0135337868 |
| Item Weight | 2.86 pounds (1.3 kg) |
| Dimensions | 7.38 x 1.82 x 9 inches (18.7 x 4.6 x 22.9 cm) |
MAHSULOT TAVSIFI
Machine Learning Foundations, Volume 1: Supervised Learning
Xaridor savollari va javoblari
-
Savol:
What topics are covered in this book?
Javob: The book covers core ideas of supervised machine learning, including model capacity, bias-variance tradeoff, classification, regression, and foundational algorithms. -
Savol:
Is prior knowledge of machine learning necessary to understand this book?
Javob: No, the book is designed to be accessible for beginners while also providing depth for advanced learners. -
Savol:
Are there practical exercises included in the book?
Javob: Yes, each chapter includes exercises that reinforce understanding through both theoretical and programming-based tasks.
Intelligence & Semantics Editorial Review
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UZS 1157301
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Xususiyatlar va Afzalliklar
- Comprehensive guide to core machine learning algorithms and concepts.
- Balances mathematical rigor with practical implementation in Python.
- Includes hundreds of annotated code examples available on GitHub.
- Covers essential background in linear algebra, calculus, and statistics.
- Offers hands-on experience with industry-standard tools like Scikit-Learn and XGBoost.
- Addresses real-world challenges in data such as imbalanced datasets and missing data.
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