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Product Details 基本信息 ISBN-13 书号 9783030243586 Author 作者 Oneto Format 版本 精装 Pages Number 页数 132页 Publisher 出版社 Springer Publication Date 出版日期 1800-01-01 Product Dimensions 商品尺寸 9.2 x 6.1 x 0.3 cm Shipping Weight 商品重量 830g Language 语种 英语
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【预订】Model Selection and Error Estimation in a Nutshell 97830 美国库房发货，通常付款后3-5周到货！
Product Details 基本信息 ISBN-13 书号 9783030243616 Author 作者 Oneto Format 版本 平装-胶订 Pages Number 页数 132页 Publisher 出版社 Springer Berlin Heidelberg Publication Date 出版日期 2020-08-14 Language 语种 英语 Book Contents 内容简介 How can we select the best performing data-driven model How can we rigorously estimate its generalization error? Statistical learning theory answers these questions by deriving non-asymptotic bounds on the generalization error of a model or, in other words, by upper bounding the true error of the learned model based just on quantities computed on the available data. However, for a long time, Statistical learning theory has been considered only an abstract theoretical framework, useful for inspiring new learning approaches, but with limited applicability to practical problems. The purpose of this book is to give an intelligible overview of the problems of model selectio
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Product Details 基本信息 ISBN-13 书号 9783030438821 Author 作者 Oneto Format 版本 精装 Pages Number 页数 221页 Publisher 出版社 Springer Berlin Heidelberg Publication Date 出版日期 2020-04-04 Language 语种 英语 Book Contents 内容简介 This book offers a timely snapshot and extensive practical and theoretical insights into the topic of learning from data. Based on the tutorials presented at the INNS Big Data and Deep Learning Conference, INNSBDDL2019, held on April 16-18, 2019, in Sestri Levante, Italy, the respective chapters cover advanced neural networks, deep architectures, and supervised and reinforcement machine learning models. They describe important theoretical concepts, presenting in detail all the necessary mathematical formalizations, and offer essential guidance on their use in current big data research.
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Product Details 基本信息 ISBN-13 书号 9783030438852 Author 作者 Luca Oneto Format 版本 平装-胶订 Pages Number 页数 221页 Publisher 出版社 Springer Publication Date 出版日期 2021-04-04 Language 语种 英语 Book Contents 内容简介 This book offers a timely snapshot and extensive practical and theoretical insights into the topic of learning from data. Based on the tutorials presented at the INNS Big Data and Deep Learning Conference, INNSBDDL2019, held on April 16-18, 2019, in Sestri Levante, Italy, the respective chapters cover advanced neural networks, deep architectures, and supervised and reinforcement machine learning models. They describe important theoretical concepts, presenting in detail all the necessary mathematical formalizations, and offer essential guidance on their use in current big data research.
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