Mathematics for Machine Learning
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Mathematics for Machine Learning
This self-contained textbook bridges the gap between mathematical and machine learning texts by introducing mathematical concepts with a minimum of prerequisites.
Mathematics for Machine Learning
منتج #: 18149781

Mathematics for Machine Learning

منتج #: 18149781

OMR 28

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This self-contained textbook bridges the gap between mathematical and machine learning texts by introducing mathematical concepts with a minimum of prerequisites.
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Comprehensive Coverage
This book covers mathematical concepts essential for machine learning thoroughly, making it suitable for beginners to experts seeking a solid foundation in statistics, linear algebra, and calculus.
Practical Applications
Each chapter includes real-world examples and exercises, allowing readers to see how mathematical theories apply directly to modern machine learning problems, enhancing practical understanding.
Accessible Learning
Written in an engaging style, this textbook simplifies complex topics, ensuring that readers from diverse educational backgrounds can grasp fundamental concepts critical for advancing in the field of machine learning.

تفاصيل المنتج

Shop Mathematics for Machine Learning online at a best price in عمان. 110845514X
Publisher Cambridge University Press
Publication date April 23, 2020
Edition 1st
Language English
Print length 398 pages
ISBN-10 110845514X
ISBN-13 978-1108455145
Item Weight 1.76 pounds (800 grams)
Dimensions 7 x 0.88 x 10 inches (17.8 x 2.2 x 25.4 cm)
Part of series Studies in Natural Language Processing

من يجب أن يشتري؟

Suitable For
  • Aspiring Data Scientists

    This product offers essential mathematical foundations needed to understand and implement machine learning algorithms effectively.

  • University Students

    Ideal for college students pursuing degrees in computer science or related fields, enhancing their understanding of machine learning principles.

  • Professionals Upskilling

    Suitable for industry professionals looking to improve their mathematical skills related to machine learning applications and frameworks.

Not Suitable For
  • Beginner Mathematicians

    Not ideal for those with little to no mathematical knowledge, as it assumes a foundational understanding of advanced concepts.

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 أقل

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. Continue Reading

أسئلة العملاء & الإجابات

  • 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 Oman؟

    إجابه: نعم ، في يوباي Oman 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.

Computer Vision & Pattern Recognition Editorial Review

Mathematics for Machine Learning offers a structured approach for understanding the mathematical concepts crucial to machine learning. It caters to readers with varying backgrounds, emphasizing essential topics in linear algebra, calculus, and statistics. The book is well-organized and visually engaging, making complex ideas more accessible. The inclusion of supplementary material, such as freely available PDFs and Jupyter notebooks, significantly enhances the learning experience, allowing for practical exploration of topics covered. Readers appreciate that it doesn't assume advanced prior knowledge, though having some foundational math skills is beneficial. This book serves as a bridge between theoretical concepts and practical implementation in machine learning, guiding both beginners and experienced practitioners alike.

مراجعات العملاء وتقييماتهم

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إيجابيات

  • Well-structured content for varying backgrounds
  • Free access to PDFs and Jupyter notebooks
  • Visually engaging illustrations enhance understanding
  • Clear explanations simplify complex topics
  • Ideal for bridging theory and practice in ML

سلبيات

  • Not comprehensive for advanced mathematical topics

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.

OMR 28

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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.