- الصفحة الرئيسية /
- الكتب /
- الكمبيوتر والتكنولوجيا /
- علوم الكمبيوتر /
- AI & Machine Learning /
- Machine Theory /
- Data Science and Machine Learning: Mathematic...
0 ratings
منتج #:
20814225
Data Science and Machine Learning: Mathematical and Statistical Methods (Chapman & Hall/CRC Machine Learning & Pattern Recognition)
88% من المشترين سيوصون بهذا المنتج لصديق
منتج #:
20814225
ILS 248
تفاصيل السعر
باستثناء رسوم الشحن والجمارك ( سيتم احتساب رسوم الشحن والجمارك عند إتمام الشراء )
*سيتم استيراد جميع العناصر من أمريكا
60%
متوفر فى المخزون
مستورد من متجر USA
كمية:
بقي 4 فقط من المنتج في المخزن.
اطلب الآن واحصل عليه حول الجمعة, أكتوبر 09
معاملة آمنة
تعمل يوباي جاهدة لحماية أمنك وخصوصيتك. يضمن نظام أمان الدفع المتقدم لدينا السرية من خلال تشفير معلوماتك أثناء النقل باستخدام بروتوكولات AES (معايير التشفير المتقدمة) وSSL (طبقة المنافذ الآمنة). تفاصيل الدفع الخاصة بك آمنة بنسبة %100 لأننا لا نشارك تفاصيل الدفع الخاصة بك مع بائعين تابعين لجهات خارجية
أفضل شركائنا اللوجستيين
This textbook is a well-rounded, rigorous, and informative work presenting the mathematics behind modern machine learning techniques.
شحن
سريع
استرجاع
مجاني*
تغليف آمن
منتجات أصلية %100
الامتثال لمعيار PCI DSS
حاصل على شهادة ISO 27001
Note: Step Down Voltage Transformer required for using electronics products of أمريكا store (110-120). Recommended power converters اشتري الآن.
أبرز ما يلفت الانتباه
Comprehensive Coverage
This textbook offers an extensive examination of mathematical and statistical methods essential for data science and machine learning, making it ideal for students and professionals seeking thorough understanding.
Practical Applications
Real-world examples and case studies illustrate how mathematical concepts apply to data science problems, providing readers with practical insights that enhance learning and application in their projects.
Accessible Learning
The book is designed for all skill levels, using clear explanations and step-by-step approaches, ensuring that even beginners can grasp complex ideas effectively and build confidence in applying them.
تفاصيل المنتج
- Well-rounded, rigorous, and informative work on the mathematics behind modern machine learning techniques.
- Ideal for a course on data science for mathematics students at an advanced undergraduate or early graduate level.
- Fills a gap in the existing literature by presenting proofs of major theorems and providing a copious amount of Python code.
- Provides a deeper dive into data-scientific methods compared to many introductory texts.
- Focuses on mathematical understanding, with a self-contained and accessible presentation.
- Includes extensive list of exercises and worked-out examples, concrete algorithms with Python code, and full-color illustrations.
| Publisher | Chapman and Hall/CRC |
| Publication date | November 22, 2019 |
| Edition | 1st |
| Language | English |
| Print length | 538 pages |
| ISBN-10 | 1138492531 |
| ISBN-13 | 978-1138492530 |
| Item Weight | 3.73 pounds (1.69 kg) |
| Dimensions | 8.75 x 1.25 x 11 inches (22.2 x 3.2 x 27.9 cm) |
| Part of series | Chapman & Hall/Crc Machine Learning & Pattern Recognition |
من يجب أن يشتري؟
-
Students in Data Science
Ideal for university students studying data science, offering mathematical foundations and statistical methods crucial for their coursework.
-
Data Professionals
Useful for data analysts and engineers looking to deepen their understanding of machine learning and statistical methods for improved performance.
-
Researchers
Beneficial for researchers needing a solid mathematical background in statistical methods for data-driven projects and academic studies.
-
Beginners in Programming
Not suitable for programming novices, as it assumes a strong foundation in math and programming skills which may be lacking.
وصف المنتج
About This Item
Introducing "Data Science and Machine Learning: Mathematical and Statistical Methods" - the ultimate guide for anyone interested in diving deep into the world of data science and machine learning. Authored by a team of renowned experts, this book provides a comprehensive overview of the fundamental mathematical and statistical methods used in these fields. Written by Dirk P. Kroese, a Professor of Mathematics and Statistics at The University of Queensland, this book offers insights from over 120 articles and five books that cover various areas in mathematics, statistics, data science, machine learning, and Monte Carlo methods.
Dr. Kroese is a pioneer of the Cross-Entropy method, a widely acclaimed adaptive Monte Carlo technique used worldwide to solve complex estimation and optimization problems in science, engineering, and finance. Joining him is Zdravko Botev, an Australian Mathematical Science Institute Lecturer in Data Science and Machine Learning, recognized by the Australian Academy of Science with the prestigious Christopher Heyde Medal in 2018 for his distinguished research in mathematical sciences. Thomas Taimre, a Senior Lecturer of Mathematics and Statistics at The University of Queensland, contributes his expertise in applied probability, Monte Carlo methods, applied physics, and the self-mixing effect in lasers.
Lastly, Radislav Vaisman, a Lecturer of Mathematics and Statistics, brings his experience in applied probability, machine learning, and computer science to round out the team. Whether you're a beginner or already have some knowledge in the field, this book caters to all levels of expertise. With topics ranging from foundational concepts to advanced applications, this book covers it all. Gain insights into machine learning algorithms, explore data science techniques, and understand the principles behind pattern recognition.
Enhance your skills and stay up-to-date with the latest trends, best practices, and real-world case studies. Unlock the potential of data science and machine learning with this indispensable resource, available in the first edition from Chapman & HallCRC. Don't miss out on this opportunity to expand your knowledge and advance your career in the exciting field of data science and machine learning. Keywords: Chapman & HallCRC Machine Learning, Chapman & HallCRC Data Science and Machine Learning, Chapman & HallCRC Pattern Recognition 1st Edition, Machine Learning and Data Science, Data Science and Machine Learning, Pattern Recognition 1st Edition, Machine Learning and Data Science books, Data Science and Machine Learning tutorials, Pattern Recognition 1st Edition guide, Machine Learning and Data Science resources, Data Science and Machine Learning techniques, Pattern Recognition 1st Edition techniques, Machine Learning and Data Science applications, Data Science and Machine Learning algorithms, Pattern Recognition 1st Edition examples, Machine Learning and Data Science trends, Data Science and Machine Learning career, Pattern Recognition 1st Edition research, Machine Learning and Data Science tips, Data Science and Machine Learning best practices, Pattern Recognition 1st Edition case studies.
هل لديك أي استفسار؟ تحدث معنا
أسئلة العملاء & الإجابات
-
سؤال:
What is the focus of 'Data Science and Machine Learning: Mathematical and Statistical Methods'?
إجابه: The book primarily focuses on the mathematical and statistical foundations that underpin data science and machine learning. It elaborates on various methods and algorithms, illustrating the theory behind them, making it essential for students and professionals aiming to deepen their understanding of these fields. Through practical examples and case studies, readers will see how these theoretical concepts are applied in real-world scenarios, aiding in better analytical problem-solving. -
سؤال:
Who is the target audience for this book?
إجابه: This book is targeted towards students, researchers, and professionals in data science and statistics. It serves as a comprehensive resource for those looking to enhance their technical knowledge in machine learning methodologies. Whether you are pursuing academic goals or working in an industry capacity, having a foundational grasp of these mathematical and statistical principles is critical for developing effective models and interpreting data effectively. -
سؤال:
What algorithms are discussed in this edition?
إجابه: This edition delves into a range of algorithms, including linear regression, decision trees, support vector machines, and neural networks. Each method is presented with its mathematical derivation, providing readers with a thorough understanding of how and when to apply these techniques. Practical use cases are included, demonstrating how these algorithms solve complex data problems across various industries, such as healthcare, finance, and e-commerce. -
سؤال:
How does the book approach statistical concepts?
إجابه: The book systematically introduces statistical concepts by laying out the foundational theories before progressing into complex methodologies. It emphasizes concepts like probability theory, inference, and hypothesis testing, which are crucial in validating machine learning models. By engaging with these concepts, readers will learn how to effectively assess data integrity and make data-driven decisions based on statistical insights. -
سؤال:
Are there practical applications included in the book?
إجابه: Yes, the book integrates practical applications throughout its chapters. Each section contains real-world examples that showcase how mathematical and statistical methods are utilized in various fields. This context not only enhances the learning experience but also equips readers with the skills to implement these techniques in their projects or research, fostering a hands-on understanding of the subject matter. -
سؤال:
Is this book suitable for beginners in data science?
إجابه: While the book covers advanced topics in data science and machine learning, it begins with fundamental concepts, making it accessible to readers who are new to the field. Beginners will appreciate the clear explanations and structured layout, which gradually build upon each other. This way, although initially challenging, readers can gain confidence as they progress through the material. -
سؤال:
What prerequisites should readers have before diving into this book?
إجابه: Readers should ideally have a basic understanding of mathematics, particularly calculus and linear algebra, alongside a fundamental grasp of statistical concepts. Familiarity with programming in languages like Python or R is advantageous, as it enables readers to implement the algorithms discussed. This preparation will allow readers to engage more deeply with the content and effectively apply the theories in practical situations. -
سؤال:
How does the author integrate machine learning with statistical methods?
إجابه: The author effectively integrates machine learning and statistical methods by demonstrating how statistical theories can inform machine learning practices. Each chapter highlights how statistical analysis is crucial for feature selection, model evaluation, and interpretation of results. This synergy is vital for practitioners aiming to enhance model performance and ensuring that their machine learning solutions are scientifically sound. -
سؤال:
Can this book be used as a textbook for academic courses?
إجابه: Certainly! This book is an excellent resource for academic courses in data science, machine learning, or statistics. Its structured content and comprehensive coverage make it suitable for both undergraduate and graduate-level programs. Instructors can rely on its clear explanations and practical problems to engage students effectively, promoting a collaborative learning environment throughout the course. -
سؤال:
Where can I buy 'Data Science and Machine Learning: Mathematical and Statistical Methods' in Palestine?
إجابه: You can purchase 'Data Science and Machine Learning: Mathematical and Statistical Methods' at Ubuy. Ubuy offers a wide selection of books, including this edition, making it convenient for individuals in Palestine looking to expand their knowledge in data science and machine learning. With user-friendly navigation, you can easily find the book and have it delivered directly to your doorstep.
Machine Theory Editorial Review
Data Science and Machine Learning: Mathematical and Statistical Methods (Chapman & Hall/CRC Machine Learning & Pattern Recognition) offers a comprehensive exploration of the mathematical and algorithmic foundations critical for understanding data science and machine learning. The book covers essential topics such as Bayesian learning, Monte Carlo Methods, and Deep Learning, with a clean and colorful layout that aids in grasping complex notations. Readers have noted its depth and rigor, making it an excellent choice for those serious about advancing in this field. However, some mention that the documentation for the accompanying Python codes could improve to mitigate confusion during implementation.
مراجعات العملاء وتقييماتهم
45 تقييمات العملاء
-
5 نجمة
85%
-
4 نجمة
8%
-
3 نجمة
7%
-
2 نجمة
0%
-
1 نجمة
0%
أضف تقييم لهذا المنتج
شارك أفكارك مع عملاء آخرين
إيجابيات
- In-depth coverage of machine learning concepts
- Rigorous mathematical foundation
- Clean and colorful format for better understanding
- Challenging exercises enhance learning
- Valuable references listed for further study
سلبيات
- Some may find the mathematical notation challenging
منصة موثوقة وثقة كاملة للمشتري
JK
Jasmin
مشتري موثّق
“Great products and very good service: very easy and very fast international delivery.”
9 September 2026 · عبر Trustpilot
AG
Anke
مشتري موثّق
“Wonderful online shopping experience, smooth transaction from the start. Payment method works conveniently and delivery is unexpectedly fast and reliable. You go the extra mile for service. What makes this even more amazing, you deliver to Namibia. I will remain a happy Ubuy customer and will increase my purchases for sure! Thank you!”
10 September 2026 · عبر Trustpilot
H
Hazel
مشتري موثّق
“Very easy to find the products what you need, and so fast delivery, that’s why I highly recommended to others costumers to used ubuy.”
10 September 2026 · عبر Trustpilot
O
Opaleye
مشتري موثّق
“I received exactly what I ordered I was skeptical about your site because that was my first time to order. But the order came timely and neatly packaged. I was not disappointed. Thank you.”
11 September 2026 · عبر Trustpilot
AC
Adele
مشتري موثّق
“Easy to find and order what you want on the website. Delivery is quick to the UK”
8 September 2026 · عبر Trustpilot
الخروج الآمن
شحن عالمي
إسترجاع سهل
منتجات أصلية
تاريخ سعر المنتج
معلومات مهمة
- القيود: بالنسبة للمنتجات التي يتم شحنها دولياً، يُرجى ملاحظة أن أي ضمان من الشركة المصنعة قد لا يكون صالحاً؛ قد لا تتوفر خيارات خدمة الشركة المصنعة؛ قد لا تكون أدلة المنتج والتعليمات وتحذيرات السلامة مكتوبة بلغة بلد المقصد؛ قد لا يتم تصميم المنتجات (والمواد المصاحبة لها) وفقاً لمعايير بلد الوجهة والمواصفات ومتطلبات الملصقات؛ وقد لا تتوافق المنتجات مع الجهد الكهربي المستخدم في بلد الوجهة والمعايير الكهربائية الأخرى (تتطلب استخدام محوّل كهربي أو جهاز تحويل إذا كان ذلك مناسباً). المستلم مسؤول عن ضمان إمكانية استيراد المنتج بشكل قانوني إلى بلد الوجهة. عند الطلب من يوباي أو الشركات التابعة لها، يكون المستلم هو المستورد المسجل ويجب أن يلتزم بجميع القوانين واللوائح الخاصة ببلد الوجهة.
- ليست كل المنتجات المدرجة على يوباي معروضة للبيع، لأن يوباي هو محرك بحث عالمي. المنتجات تخضع للوائح التصدير / التجارة.
ILS 248
اطلب الآن واحصل عليه حول الجمعة, أكتوبر 09
هذا المنتج غير ممنوع في بلدي. (الرجاء الضغط على الرابط أعلاه إذا لم يكن هذا المنتج ممنوعاً في بلدك ، لذلك سيقوم فريقنا بمراجعته والسماح به.)
كمية:
بقي 4 فقط من المنتج في المخزن.
معاملة آمنة
نوفر لك مدفوعات مشفّرة، وحماية متكاملة للمشتري، مع الالتزام بمعايير PCI DSS وشهادة ISO 27001:2022 لضمان أعلى مستويات الأمان في كل عملية شراء.
أفضل شركائنا اللوجستيين
أسرع توصيل عبر الحدود
المميزات والفوائد
- Ideal for mathematics students at the advanced undergraduate or early graduate level
- Provides proofs of major theorems and derivations
- Includes a copious amount of Python code
- Deeper dive into data-scientific methods compared to introductory texts
- Focuses on mathematical understanding
- Extensive list of exercises and worked-out examples
ضمان Ubuy
تسوّق بثقة مع منتجات أصلية %100، ومدفوعات آمنة متوافقة مع معيار PCI DSS، وحماية بيانات معتمدة وفق ISO 27001، وشحن دولي سريع، وإرجاع مجاني*، وتغليف آمن لكل طلب.