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                <text>This open textbook fits one- or two-semester courses across fields like computer science, business, finance, and more. It blends real and fictional scenarios, in-depth coverage of data ethics and AI, and hands-on Python examples to make data science both accessible and impactful. Direct download links in the text for datasets, code snippets, and rich practice exercises help you apply core concepts in real-world contexts. &#13;
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The novel approach taken here banishes determinants to the end of the book. The text focuses on the central goal of linear algebra: understanding the structure of linear operators on finite-dimensional vector spaces. The author has taken unusual care to motivate concepts and simplify proofs. A variety of interesting exercises in each chapter helps students understand and manipulate the objects of linear algebra. Beautiful formatting creates pages with an unusually student-friendly appearance in both print and electronic versions.&#13;
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