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Introduction to Machine Learning From Math to Code
- Textbook
Published 2025
Description
Emphasizing how and why machine learning algorithms work, this introductory textbook bridges the gap between the theoretical foundations of machine learning and its practical algorithmic and code-level implementation. Over 85 thorough worked examples, in both Matlab and Python, demonstrate how algorithms are implemented and applied whilst illustrating the end result. Over 75 end-of-chapter problems empower students to develop their own code to implement these algorithms, equipping them with hands-on experience. Matlab coding examples demonstrate how a mathematical idea is converted…
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Key features
- A self-contained textbook, containing all the necessary background information as well as key machine learning topics in the same volume
- Encourages students to understand how to translate mathematical ideas into code implementation, enhancing understanding of the inner workings of machine learning algorithms
- Examples are developed without the need to rely on existing libraries or software
Keywords
About the book
- DOI https://doi.org/10.1017/9781009023870
- Subjects Communications and Signal Processing,Computer Science,Engineering,Machine Learning and Pattern Recognition
- Format: Hardback
- Publication date: 18 December 2025
- ISBN: 9781316519509
- Dimensions (mm): 254 x 178 mm
- Weight: 1.216kg
- Page extent: 578 pages
- Availability: Temporarily unavailable - no date available
- Format: Digital
- Publication date: 05 February 2026
- ISBN: 9781009023870
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