{"product_id":"tensor-decompositions-for-data-science-hardback-9781009471671","title":"Tensor Decompositions for Data Science (Hardback) 9781009471671","description":"\u003cfont face=\"Georgia\"\u003e\r\n\u003cp\u003e\u003cfont size=\"6\"\u003eTensor Decompositions for Data Science\u003c\/font\u003e\u003cbr\u003e\r\n\r\n\r\n\u003c\/p\u003e\n\u003cp\u003e\u003cem\u003eA self-contained mathematical, algorithmic, and computational treatment of tensor decomposition, including examples using real datasets.\u003c\/em\u003e\u003c\/p\u003e\r\n\r\n\r\n\u003cp\u003e\u003cfont size=\"4\"\u003eGrey Ballard (Author), Tamara G. Kolda (Author)\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003e9781009471671, Cambridge University Press\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003eHardback, published 26 June 2025\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003e419 pages\u003cbr\u003e26 x 18.1 x 2.7 cm, 1.06 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'Tensors play a crucial role in numerous aspects of data science, including machine learning, computer vision, natural language processing, data compression, anomaly detection, social science, computational neuroscience, materials science, microbiology, and many others. This book provides an accessible yet thorough exploration of tensor representations for complex data. The authors meticulously cover key variants, foundational theories, and practical algorithms - making complex concepts understandable for readers at different levels of expertise.' Rebecca Willett, University of Chicago\u003c\/font\u003e\u003c\/em\u003e\u003c\/p\u003e\r\n\r\n\u003cp align=\"justify\"\u003e\u003cstrong\u003e\u003cfont size=\"3\"\u003eTensors are essential in modern day computational and data sciences. This book explores the foundations of tensor decompositions, a data analysis methodology that is ubiquitous in machine learning, signal processing, chemometrics, neuroscience, quantum computing, financial analysis, social science, business market analysis, image processing, and much more. In this self-contained mathematical, algorithmic, and computational treatment of tensor decomposition, the book emphasizes examples using real-world downloadable open-source datasets to ground the abstract concepts. Methodologies for 3-way tensors (the simplest notation) are presented before generalizing to d-way tensors (the most general but complex notation), making the book accessible to advanced undergraduate and graduate students in mathematics, computer science, statistics, engineering, and physical and life sciences. Additionally, extensive background materials in linear algebra, optimization, probability, and statistics are included as appendices.\u003c\/font\u003e\u003c\/strong\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003ePreface\u003cbr\u003e I. Tensor Basics: 1. Tensors and their subparts\u003cbr\u003e 2. Indexing and reshaping tensors\u003cbr\u003e 3. Tensor operations\u003cbr\u003e II. Tucker Decomposition: 4. Tucker decomposition\u003cbr\u003e 5. Tucker tensor structure\u003cbr\u003e 6. Tucker algorithms\u003cbr\u003e 7. Tucker approximation error\u003cbr\u003e 8. Tensor train decomposition\u003cbr\u003e III. CP Decomposition: 9. Canonical polyacidic (CP) decomposition\u003cbr\u003e 10. Kruskal tensor structure\u003cbr\u003e 11. CP alternating least squares (CP-ALS) optimization\u003cbr\u003e 12. CP gradient-based optimization (CP-OPT)\u003cbr\u003e 13. CP nonlinear least squares (CP-NLS) optimization\u003cbr\u003e 14. CP algorithms for incomplete or scarce data\u003cbr\u003e 15. Generalized CP (GCP) decomposition\u003cbr\u003e 16. CP tensor rank and special topics\u003cbr\u003e IV. Closing Observations: 17. Closing observations\u003cbr\u003e V. Review Materials: A. Numerical linear algebra\u003cbr\u003e B. Optimization principles and methods\u003cbr\u003e C. Some statistics and probability\u003cbr\u003e Bibliography\u003cbr\u003e Index.\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003eSubject Areas: Numerical analysis [\u003ca title=\"See our other books on Numerical analysis\" href=\"https:\/\/freshlyprintedbooks.co.uk\/search?q=%22Numerical%20analysis%20%5BPBKS%5D%22\"\u003ePBKS\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":52453561106712,"sku":"9781009471671","price":47.69,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0730\/2037\/5320\/files\/9781009471671i.jpg?v=1785286627","url":"https:\/\/freshlyprintedbooks.co.uk\/products\/tensor-decompositions-for-data-science-hardback-9781009471671","provider":"Freshly Printed Books","version":"1.0","type":"link"}