{"product_id":"linear-algebra-for-data-science-machine-learning-and-signal-processing-hardback-9781009418140","title":"Linear Algebra for Data Science, Machine Learning, and Signal Processing (Hardback) 9781009418140","description":"\u003cfont face=\"Georgia\"\u003e\r\n\u003cp\u003e\u003cfont size=\"6\"\u003eLinear Algebra for Data Science, Machine Learning, and Signal Processing\u003c\/font\u003e\u003cbr\u003e\r\n\r\n\r\n\u003c\/p\u003e\n\u003cp\u003e\u003cem\u003eMaster matrix methods via engaging data-driven applications, aided by classroom-tested quizzes, homework exercises and online Julia demos.\u003c\/em\u003e\u003c\/p\u003e\r\n\r\n\r\n\u003cp\u003e\u003cfont size=\"4\"\u003eJeffrey A. Fessler (Author), Raj Rao Nadakuditi (Author)\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003e9781009418140, Cambridge University Press\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003eHardback, published 16 May 2024\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003e452 pages\u003cbr\u003e25.1 x 17.6 x 3 cm, 0.93 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'Great textbook, good also for Senior Students who have discovered towards the end of their studies that Linear Algebra is the foundation of Machine Learning, Computer Graphics, Computer Vision and more' Gudrun Socher, Munich University of Applied Sciences\u003c\/font\u003e\u003c\/em\u003e\u003c\/p\u003e\r\n\r\n\u003cp align=\"justify\"\u003e\u003cstrong\u003e\u003cfont size=\"3\"\u003eMaximise student engagement and understanding of matrix methods in data-driven applications with this modern teaching package. Students are introduced to matrices in two preliminary chapters, before progressing to advanced topics such as the nuclear norm, proximal operators and convex optimization. Highlighted applications include low-rank approximation, matrix completion, subspace learning, logistic regression for binary classification, robust PCA, dimensionality reduction and Procrustes problems. Extensively classroom-tested, the book includes over 200 multiple-choice questions suitable for in-class interactive learning or quizzes, as well as homework exercises (with solutions available for instructors). It encourages active learning with engaging 'explore' questions, with answers at the back of each chapter, and Julia code examples to demonstrate how the mathematics is actually used in practice. A suite of computational notebooks offers a hands-on learning experience for students. This is a perfect textbook for upper-level undergraduates and first-year graduate students who have taken a prior course in linear algebra basics.\u003c\/font\u003e\u003c\/strong\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003e1. Getting started\u003cbr\u003e 2. Introduction to Matrices\u003cbr\u003e 3. Matrix factorization: eigendecomposition and SVD\u003cbr\u003e 4. Subspaces, rank and nearest-subspace classification\u003cbr\u003e 5. Linear least-squares regression and binary classification\u003cbr\u003e 6. Norms and Procrustes problems\u003cbr\u003e 7. Low-rank approximation and multidimensional scaling\u003cbr\u003e 8. Special matrices, Markov chains and PageRank\u003cbr\u003e 9. Optimization basics and logistic regression\u003cbr\u003e 10. Matrix completion and recommender systems\u003cbr\u003e 11. Neural network models\u003cbr\u003e 12. Random matrix theory, signal+ noise matrices, and phase transitions.\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003eSubject Areas: Pattern recognition [\u003ca title=\"See our other books on Pattern recognition\" href=\"https:\/\/freshlyprintedbooks.co.uk\/search?q=%22Pattern%20recognition%20%5BUYQP%5D%22\"\u003eUYQP\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":52458403594520,"sku":"9781009418140","price":42.99,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0730\/2037\/5320\/files\/9781009418140i.jpg?v=1785372295","url":"https:\/\/freshlyprintedbooks.co.uk\/products\/linear-algebra-for-data-science-machine-learning-and-signal-processing-hardback-9781009418140","provider":"Freshly Printed Books","version":"1.0","type":"link"}