{"product_id":"introduction-to-machine-learning-from-math-to-code-hardback-9781316519509","title":"Introduction to Machine Learning; From Math to Code (Hardback) 9781316519509","description":"\u003cfont face=\"Georgia\"\u003e\r\n\u003cp\u003e\u003cfont size=\"6\"\u003eIntroduction to Machine Learning\u003c\/font\u003e\u003cbr\u003e\r\n\u003cfont size=\"5\"\u003eFrom Math to Code\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cem\u003eExplore how and why machine learning algorithms work with this self-contained, hands-on introduction using Matlab and Python.\u003c\/em\u003e\u003c\/p\u003e\r\n\r\n\r\n\u003cp\u003e\u003cfont size=\"4\"\u003eRuye Wang (Author)\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003e9781316519509, Cambridge University Press\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003eHardback, published 18 December 2025\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003e578 pages\u003cbr\u003e25.4 x 17.8 x 3.2 cm, 1.216 kg\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\r\n\r\n\u003cp align=\"justify\"\u003e\u003cem\u003e\u003cfont size=\"3\"\u003e'This is an excellent book for an introduction to machine learning. The chapters are well organized, and the mathematical treatment strikes a thoughtful balance between rigor and accessibility. The examples and problem sets are carefully designed and effectively reinforce the core concepts.' Hom Nath Gharti, Queen's University\u003c\/font\u003e\u003c\/em\u003e\u003c\/p\u003e\r\n\r\n\u003cp align=\"justify\"\u003e\u003cstrong\u003e\u003cfont size=\"3\"\u003eEmphasizing 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 from equations to code, and provide a jumping off point for students, supported by in-depth coverage of essential mathematics including multivariable calculus, linear algebra, probability and statistics, numerical methods, and optimization. Accompanied online by instructor lecture slides, downloadable Python code and additional appendices, this is an excellent introduction to machine learning for senior undergraduate and graduate students in Engineering and Computer Science.\u003c\/font\u003e\u003c\/strong\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003ePart I. Mathematical Foundations: 1. Solving Equations\u003cbr\u003e 2. Unconstrained Optimization\u003cbr\u003e 3. Constrained Optimization\u003cbr\u003e Part II. Regression: 4. Bias-Variance Tradeoff and Overfitting vs Underfitting\u003cbr\u003e 5. Linear Regression\u003cbr\u003e 6. Nonlinear Regression\u003cbr\u003e 7. Logistic and Softmax Regression\u003cbr\u003e 8. Gaussian Process Regression and Classification\u003cbr\u003e Part III. Feature Extraction: 9. Feature Selection\u003cbr\u003e 10. Principal Component Analysis\u003cbr\u003e 11. Variations of PCA\u003cbr\u003e 12. Independent Component Analysis\u003cbr\u003e Part IV. Classification: 13. Statistic Classification\u003cbr\u003e 14. Support Vector machine\u003cbr\u003e 15. Clustering Analysis\u003cbr\u003e 16. Hierarchical Classifiers\u003cbr\u003e 17. Biologically Inspired Networks\u003cbr\u003e 18. Perceptron-Based Networks\u003cbr\u003e 19. Competition-Based Networks\u003cbr\u003e Part VI. Reinforcement Learning: 20. Introduction to Reinforcement Learning\u003cbr\u003e Part VII. Large Language Models: 21. Large Language Models\u003cbr\u003e Appendix A. A Review of Linear Algebra\u003cbr\u003e Appendix B. A Review of Probability and Statistics.\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003eSubject Areas: Communications engineering \/ telecommunications [\u003ca title=\"See our other books on Communications engineering \/ telecommunications\" href=\"https:\/\/freshlyprintedbooks.co.uk\/search?q=%22Communications%20engineering%20\/%20telecommunications%20%5BTJK%5D%22\"\u003eTJK\u003c\/a\u003e]\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\r\n\u003c\/font\u003e","brand":"Cambridge University Press","offers":[{"title":"Brand New","offer_id":52462965096728,"sku":"9781316519509","price":67.79,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0730\/2037\/5320\/files\/9781316519509i.jpg?v=1785543680","url":"https:\/\/freshlyprintedbooks.co.uk\/products\/introduction-to-machine-learning-from-math-to-code-hardback-9781316519509","provider":"Freshly Printed Books","version":"1.0","type":"link"}