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Linear Algebra and Optimization for Machine LearningA Textbook

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Linear Algebra and Optimization for Machine Learning978-3-030-40344-7

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Optimization Basics: A Machine Learning View, models for classification were often motivated as modifications of the least-squares regression model. The main difference between least-squares regression and classification is that the predicted target variable is numerical in the former, whereas it is discrete (typically binary) in the latter. T

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Textbook 2020near algebra methods with examples from machine learning differentiates this book from generic volumes on linear algebra. The focus is clearly on the most relevant aspects of linear algebra for machine learning and to teach readers how to apply these concepts..2. Optimization and its applications: M

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查看完整版本: Titlebook: Linear Algebra and Optimization for Machine Learning; A Textbook Charu C. Aggarwal Textbook 2020 Springer Nature Switzerland AG 2020 Linear