Mathematics of Deep Learning: An Introduction (De Gruyter Textbook)

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Publisher ‏ : ‎ De Gruyter; 1st edition (April 27, 2023)
Language ‏ : ‎ English
Perfect Paperback ‏ : ‎ 132 pages
ISBN-10 ‏ : ‎ 3111024318
ISBN-13 ‏ : ‎ 978-3111024318
Item Weight ‏ : ‎ 8 ounces
Dimensions ‏ : ‎ 7 x 0.25 x 10 inches

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The field of deep learning has been rapidly growing in recent years, with applications in a wide range of fields such as computer vision, natural language processing, and robotics. However, understanding the mathematical principles behind deep learning can be challenging for many students and practitioners.

In our new textbook, “Mathematics of Deep Learning: An Introduction,” published by De Gruyter, we aim to provide a comprehensive overview of the mathematical foundations of deep learning. This book is designed for students and researchers who are interested in gaining a deeper understanding of the underlying principles of deep learning algorithms.

The book covers a wide range of topics, including linear algebra, calculus, probability theory, and optimization, all of which are essential for understanding how deep learning models work. Each chapter includes detailed explanations, examples, and exercises to help readers grasp the key concepts and techniques.

Whether you are a student looking to learn more about the mathematical aspects of deep learning or a practitioner seeking to enhance your knowledge and skills, “Mathematics of Deep Learning: An Introduction” will provide you with the necessary tools to navigate the complex world of deep learning algorithms.

Get your copy of “Mathematics of Deep Learning: An Introduction” today and unlock the power of mathematics in deep learning!
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