Mathematics for Machine Learning 1st Edition | Marc Peter Deisenroth | 978-1108455145 | Paperback

Mathematics for Machine Learning book by Marc Peter Deisenroth is one of the most sought-after titles in Computer Science & Programming. As a leading programming textbook, coding guide, developer reference, software handbook, this book is trusted by students, professionals, and practitioners worldwide. Nybookshub brings you this authentic 1st Edition Paperback edition with fast global shipping.

About This Book

Mathematics for Machine Learning book is a definitive Computer Science & Programming resource written by Marc Peter Deisenroth, A. Aldo Faisal, Cheng Soon Ong. This 1st Edition edition delivers comprehensive coverage of core concepts, real-world applications, and the latest developments in the field. Whether you are a student, researcher, or working professional, this book serves as an indispensable reference and programming textbook.

• Author: Marc Peter Deisenroth, A. Aldo Faisal, Cheng Soon Ong
• Edition: 1st Edition
• Format / Binding: Paperback
• ISBN: 978-1108455145
• Pages: 518
• Subject: Computer Science & Programming
• Language: English
• Publisher: Leading Academic Publisher
• Sold by: Nybookshub

What You Will Learn

Reading Mathematics for Machine Learning book gives you a structured, expert-guided path through Computer Science & Programming. Key learning outcomes include:

• Deep understanding of core theories and foundational principles in Computer Science & Programming
• Practical, real-world techniques directly applicable to academic and professional settings
• Case studies, worked examples, and exercises that reinforce key concepts
• Up-to-date knowledge reflecting the latest standards and practices in the field
• A reliable reference you can return to throughout your career or studies

About the Author

Marc Peter Deisenroth, A. Aldo Faisal, Cheng Soon Ong bring decades of combined academic research and professional expertise to this work. Widely recognised authorities in Computer Science & Programming, their writing style balances scholarly rigour with practical accessibility — making complex topics understandable without sacrificing depth.

Why Buy from Nybookshub?

• ? 100% Authentic Edition — publisher-original, not a reprint or photocopy
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• ? Competitive Pricing — best price on Mathematics for Machine Learning book with no hidden fees
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Frequently Asked Questions (FAQ)

Is this the genuine/original edition of Mathematics for Machine Learning 1st Edition?

Yes, absolutely. Every copy of Mathematics for Machine Learning sold by Nybookshub is a 100% authentic, publisher-original edition — not a reprint, photocopy, or unauthorised reproduction. You receive the exact same book you would find in an academic bookstore.

Who is the author of Mathematics for Machine Learning 1st Edition?

This book is authored by Marc Peter Deisenroth and co-authors (Marc Peter Deisenroth, A. Aldo Faisal, Cheng Soon Ong). The author(s) are recognised experts in Computer Science & Programming and the content reflects their extensive academic and professional expertise.

What format and binding is this edition?

This listing is for the Paperback edition. The book contains 518 pages and carries ISBN 978-1108455145. Please verify the ISBN matches your requirement before ordering, especially if your institution specifies a particular edition.

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Yes. Nybookshub ships Mathematics for Machine Learning worldwide including the US, UK, Canada, Australia, UAE, India, and most countries globally. Expedited and standard shipping options are available at checkout.

How long will delivery take?

Delivery timelines depend on your location and chosen shipping method. Orders are dispatched promptly and full tracking information is provided. International deliveries typically arrive within 7–21 business days depending on the destination country.

Can I use this book for my university or professional course?

Yes. Mathematics for Machine Learning is widely used across universities, professional certification programmes, and self-study curricula in Computer Science & Programming. Always confirm with your institution that this edition number matches the prescribed course material.

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