{"product_id":"mathematical-theories-of-machine-learning-theory-and-applications-springer-nature-switzerland-ag-9783030170783-bin-shi","title":"Mathematical Theories of Machine Learning - Theory and Applications","description":"\u003cp\u003eDiscover the intricate world of machine learning with \"Mathematical Theories of Machine Learning - Theory and Applications\" by Bin Shi. Published by Springer Nature Switzerland AG in 2020, this insightful paperback spans 133 pages, delving into advanced mathematical concepts that underpin machine learning technologies.\u003c\/p\u003e \u003cp\u003eIn this comprehensive volume, the author explores subspace clustering, addressing the challenges posed by noisy and incomplete data. This topic is particularly relevant for those working with real-world data influenced by stochastic Gaussian noise and missing entries. Bin Shi's expertise provides readers with a solid foundation in both theory and practical applications, making this book an essential resource for students, researchers, and professionals in the field.\u003c\/p\u003e \u003cp\u003eEnhance your understanding of machine learning with this essential guide that bridges the gap between theoretical mathematics and practical machine learning applications.\u003c\/p\u003e","brand":"Bin Shi","offers":[{"title":"Default Title","offer_id":52268905300310,"sku":"9783030170783","price":90.93,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0886\/3206\/6390\/files\/9783030170783.jpg?v=1767802245","url":"https:\/\/www.englishbook.fi\/products\/mathematical-theories-of-machine-learning-theory-and-applications-springer-nature-switzerland-ag-9783030170783-bin-shi","provider":"Bookshop","version":"1.0","type":"link"}