منتج #:
218689248
Mathematics for Machine Learning
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منتج #:
218689248
BHD 26
تفاصيل السعر
باستثناء رسوم الشحن والجمارك ( سيتم احتساب رسوم الشحن والجمارك عند إتمام الشراء )
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معاملة آمنة
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أفضل شركائنا اللوجستيين
This self-contained textbook bridges the gap between mathematical and machine learning texts by introducing mathematical concepts with a minimum of prerequisites.
شحن
سريع
استرجاع
مجاني*
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منتجات أصلية %100
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Comprehensive Coverage
Covers essential mathematics concepts crucial for machine learning, making it accessible for beginners while providing depth for advanced practitioners, ensuring a well-rounded understanding of the subject.
Practical Applications
Emphasizes real-world applications and examples, helping users to directly relate mathematical concepts to machine learning problems, enhancing retention and practical skill development.
Interactive Learning
Incorporates interactive elements such as exercises and quizzes, fostering an engaging learning environment that promotes active participation and reinforces understanding of complex mathematical ideas.
تفاصيل المنتج
| Publisher | Cambridge University Press |
| Publication date | 23 April 2020 |
| Language | English |
| Print length | 390 pages |
| ISBN-10 | 110845514X |
| ISBN-13 | 978-1108455145 |
| Dimensions | 17.78 x 2.24 x 25.4 cm |
| Part of series | Studies in Natural Language Processing |
من يجب أن يشتري؟
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Aspiring Data Scientists
Ideal for those starting in data science, needing foundational math concepts relevant to machine learning applications.
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Engineers Transitioning Fields
Beneficial for engineers looking to pivot into machine learning and requiring a solid understanding of mathematical principles.
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Self-Learners
Perfect for self-motivated individuals seeking structured learning resources to grasp the mathematical aspects of machine learning.
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Complete Beginners
Not suitable for those with no prior mathematical background, as some concepts may be too advanced to understand.
وصف المنتج
Mathematics for Machine Learning
About This Item
Introducing the Mathematics for Machine Learning 1st Edition As the field of machine learning continues to revolutionize various industries, it is essential to have a solid understanding of the mathematical concepts that underpin this powerful technology. The Mathematics for Machine Learning 1st Edition is a comprehensive textbook that covers all the key mathematical foundations needed for successful implementation and application of machine learning algorithms. With endorsements from esteemed experts in the field, such as Joelle Pineau from McGill University and Christopher Bishop from Microsoft Research Cambridge, this book comes highly recommended for both beginners and experienced machine learning researchers and engineers. This self-contained textbook is designed to be accessible to a wide range of readers, with a minimum of prerequisites. It starts with a thorough introduction to linear algebra, which serves as the basis for many machine learning techniques.
From there, it delves into topics such as analytic geometry, matrix decompositions, vector calculus, optimization, probability, and statistics – all of which are crucial for developing a strong understanding of machine learning algorithms. Whether you are a student, a colleague, or simply someone interested in building a solid foundation in machine learning, this book will be an invaluable resource. It presents the necessary mathematical concepts in a clear and concise manner, making it easy to grasp complex ideas and apply them to real-world scenarios. The Mathematics for Machine Learning 1st Edition is not just a tutorial; it is a comprehensive reference text that you can turn to time and time again. It will help you gain a deeper understanding of the mathematical principles behind machine learning algorithms, enabling you to unlock the full potential of this transformative technology. Don't miss out on this essential resource for anyone interested in machine learning.
Order your copy of the Mathematics for Machine Learning 1st Edition today and take your understanding of this exciting field to new heights.
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Product Buying Guide
Are you a data science or computer science student or professional looking to understand the core mathematical concepts essential for machine learning? The Mathematics for Machine Learning 1st Edition is a self-contained textbook that bridges the gap between mathematical and machine learning texts, making it easier to grasp the fundamental tools needed for machine learning. Whether you have a mathematical background or are learning these concepts for the first time, this book offers a practical and intuitive approach to understanding and applying mathematical concepts in the context of machine learning.
Product Specifications
- Author: Marc Peter Deisenroth, A Aldo Faisal, and Cheng Soon Ong
- Publication Date: May 8, 2020
- Publisher: Cambridge University Press
- Paperback: 402 pages
- Language: English
- ISBN-10: 110845514X
- ISBN-13: 978-1108455145
Key Features
- Bridges the gap between mathematical and machine learning texts
- Introduces mathematical concepts with minimal prerequisites
- Derives central machine learning methods including linear regression, principal component analysis, Gaussian mixture models, and support vector machines
- Includes worked examples and exercises for practical understanding
- Offers programming tutorials on the book's website
Usage Scenarios
- Ideal for data science or computer science students seeking to understand mathematical concepts essential for machine learning
- Suitable for professionals looking to enhance their understanding and practical experience with applying mathematical concepts in the context of machine learning
- Useful for individuals with a mathematical background as well as for those learning these concepts for the first time
Usage Scenarios
- Competitor 1
- Competitor 2
- Competitor 3
Some User Review
- The book effectively bridges the gap between mathematical concepts and machine learning, providing a straightforward approach to understanding and applying these concepts.
- The inclusion of programming tutorials on the book's website is exceptionally helpful for practical implementation and reinforcement of the learned concepts.
- The worked examples and exercises contribute significantly to building a strong understanding of the mathematical tools in the context of machine learning.
Competitors
- The price of the Mathematics for Machine Learning 1st Edition is competitive compared to similar textbooks in the market, offering a cost-effective choice for learning essential mathematical concepts for machine learning.
Buying Considerations
- Consider your level of mathematical background or familiarity with the concepts when purchasing this book to ensure that it meets your learning needs and objectives.
- Take advantage of the programming tutorials offered on the book's website to enhance practical experience and implementation of the mathematical concepts in machine learning.
Conclusion
The Mathematics for Machine Learning 1st Edition is a valuable resource for students and professionals seeking a comprehensive understanding of the fundamental mathematical tools required for machine learning. With its practical approach, intuitive explanations, and inclusion of programming tutorials, this self-contained textbook is an excellent choice for anyone looking to bridge the gap between mathematical and machine learning texts.
عرض أقلAre you a data science or computer science student or professional looking to understand the core mathematical concepts essential for machine learning? The Mathematics for Machine Learning 1st Edition is a self-contained textbook that bridges the gap between mathematical and machine learning texts, making it easier to grasp the fundamental tools needed for machine learning. Whether you have a mathematical background or are learning these concepts for the first time, this book offers a practical and intuitive approach to understanding and applying mathematical concepts in the context of machine learning. Continue Reading
أسئلة العملاء & الإجابات
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سؤال:
كيف تتسوق Mathematics for Machine Learning عبر الانترنت من يوباى?
إجابه: من السهل التسوق في Mathematics for Machine Learning عبر الإنترنت من يوباي. كل ما عليك فعله هو البحث عن المنتج واختيار طريقة الشحن الخاصة بك أثناء الدفع وسيتم توصيله الى عنوانك -
سؤال:
هل Mathematics for Machine Learning متوفر للتسوق عبر الإنترنت في Bahrain؟
إجابه: نعم ، في يوباي Bahrain هذا المنتج متاح لك للتسوق بسعر مناسب. Mathematics for Machine Learning غير متوفر محليًا ولكن يمكنك الوثوق بنا بخدماتنا للشحن السريع. -
سؤال:
كم من الوقت يستغرق الحصول على المنتج بعد تقديم الطلب؟
إجابه: يختلف وقت تسليم المنتج الذي طلبته حسب ما طلبته وطريقة الشحن التي اخترتها. يتم ذكر وقت التسليم المقدر أثناء عملية الدفع ، لذا كن مرتاحًا أثناء التسوق.
English edition Marc Peter Deisenroth Format: Paperback Editorial Review
**** "Mathematics for Machine Learning" has garnered Considerable attention from readers, particularly those with an academic background in computer science or related fields. Many customers appreciate the clarity and relevance of the mathematical concepts presented, praising it as one of the best resources for understanding the mathematics crucial for machine learning applications. The book addresses a variety of topics, including vectors, matrices, linear algebra, and probability theory, and presents them in a structured manner that balances theory and practical applications. Readers commend its engaging writing style, which makes complex mathematical ideas more accessible, particularly for those with a foundational understanding of math. The book includes practical examples that relate directly to machine learning, which helps reinforce the theoretical concepts. Additionally, exercises with solutions available on GitHub enhance the learning experience, allowing readers to test their comprehension. However, some feedback suggests that the book may not fully align with its claim of being suitable for "evening learners," as it introduces advanced topics that might require a stronger mathematical foundation than merely high school mathematics. A few readers found the theoretical sections somewhat dense, with a lack of seamless integration between concepts and exercises, which may hinder understanding for some learners. While it is acknowledged that the book provides essential mathematical tools for the development of machine learning skills, clarity and pedagogical coherence were points of contention for several users. Overall, "Mathematics for Machine Learning" is well-received by those looking to deepen their understanding of the mathematical underpinnings of machine learning, though it may require a certain level of mathematical maturity for optimal comprehension. **
مراجعات العملاء وتقييماتهم
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إيجابيات
- Clear and well-structured presentation of essential mathematical concepts.
- Strong focus on practical applications relevant to machine learning.
- Engaging writing style that makes the material enjoyable to read.
- Includes exercises with solutions to facilitate self-testing and learning.
سلبيات
- May be too advanced for individuals without a solid mathematical foundation.
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.
BHD 26
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:
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
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المميزات والفوائد
- Fundamental mathematical tools needed to understand machine learning
- Self-contained textbook for building intuition and practical experience
- Bridges gap between mathematical and machine learning texts
- Introduces mathematical concepts with a minimum of prerequisites
- Chapter exercises and programming tutorials available on the book's website
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.