{"product_id":"9781009123235","title":"Random Matrix Methods for Machine Learning","description":"\u003cp\u003eThis book presents a unified theory of random matrices for applications in machine learning, offering a large-dimensional data vision that exploits concentration and universality phenomena. This enables a precise understanding, and possible improvements, of the core mechanisms at play in real-world machine learning algorithms. The book opens with a thorough introduction to the theoretical basics of random matrices, which serves as a support to a wide scope of applications ranging from SVMs, through semi-supervised learning, unsupervised spectral clustering, and graph methods, to neural networks and deep learning. For each application, the authors discuss small- versus large-dimensional intuitions of the problem, followed by a systematic random matrix analysis of the resulting performance and possible improvements. All concepts, applications, and variations are illustrated numerically on synthetic as well as real-world data, with MATLAB and Python code provided on the accompanying website.\u003c\/p\u003e","brand":"Cambridge University Press","offers":[{"title":"Default Title","offer_id":48699656470763,"sku":"00000_00000_00000_00000","price":173.96,"currency_code":"SGD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0758\/4484\/5803\/files\/9781009123235-1.jpg?v=1781647363","url":"https:\/\/kinokuniya.com.sg\/products\/9781009123235","provider":"Books Kinokuniya Singapore","version":"1.0","type":"link"}