This textbook explores applications of linear algebra in data science at an introductory level, showing readers how the two are deeply connected. The authors accomplish this by offering exercises that escalate in complexity, many of which incorporate MATLAB. Practice projects appear as well for students to better understand the real-world applications of the material covered in a standard linear algebra course. Some topics covered include singular value decomposition, convolution, frequency filtering, and neural networks. Linear Algebra in Data Science is suitable as a supplement to a standard linear algebra course.
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Langue Anglais ● Format EPUB ● ISBN 9783031549083 ● Maison d’édition Springer International Publishing ● Publié 2024 ● Téléchargeable 3 fois ● Devise EUR ● ID 9455713 ● Protection contre la copie Adobe DRM
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