Linear Algebra Data Science Machine Learning Calder Olver Springer HC Inscribed
$ 21.1
Description
Linear Algebra Data Science Machine Learning Calder Olver Springer HC Inscribed. Linear Algebra, Data Science, and Machine Learning — Calder & Olver (Springer, 2025). Jeff Calder & Peter J. Olver · University of Minnesota. Written byJeff Calder (Professor, School of Mathematics, University of Minnesota; Ph.D. ). Linear Algebra, Data Science, and Machine Learning — Calder & Olver (Springer, 2025) Mathematics · Data Science · Machine Learning · Springer UTMT Inscribed Copy Hardcover Springer · 2025 First Printing · ~625 pp Jeff Calder & Peter J. Olver · University of Minnesota Linear Algebra, Data Science, and Machine Learning A rigorous, self-contained introduction to modern data analysis A brand-new (2025) Springer graduate/advanced-undergraduate text that builds the linear algebra, optimization, probability, and graph theory behind modern machine learning from the ground up — with a presentation inscription and two signatures inside. Springer · Undergraduate Texts in Mathematics & Technology · hardcover · pub. 26 Aug 2025 · ~625 pp · ISBN 978-3-031-93763-7 Inscribed Presentation Copy — Please Read This copy carries a handwritten presentation inscription on the front endpaper: "To Bill — In appreciation of your friendship and inspiration," followed by two signatures and dated September 2025 . The book has two authors (Jeff Calder and Peter J. Olver), and the inscription is dated the month after the book's late-August 2025 release — consistent with an author presentation copy. In fairness to buyers: the signatures are stylized and not clearly legible , and this copy is offered as an inscribed copy without third-party authentication . I am not certifying whose signatures these are — the inscription is pictured in the photos so you can evaluate it yourself. Priced and described accordingly. About the Book Linear Algebra, Data Science, and Machine Learning is a mathematically rigorous introduction to modern machine learning and data analysis, pitched at the advanced-undergraduate / beginning-graduate level. It is self-contained and assumes minimal prerequisites: beyond basic calculus, the underlying mathematics — linear algebra, optimization, elementary probability, graph theory, and statistics — is developed from scratch, in a form tailored to data-science applications. The book emphasizes how and why algorithms work alongside their practical use. Its linear-algebra coverage is deliberately ordered and selected around the tools most used in contemporary machine learning. Companion Python notebooks are provided via a GitHub site (QR codes / links in the text), with exercises at the end of each section and student solutions available online. Authors & Series Written by Jeff Calder (Professor, School of Mathematics, University of Minnesota; Ph.D. Michigan) and Peter J. Olver (University of Minnesota), a widely known figure in applied mathematics. It appears in Springer's Undergraduate Texts in Mathematics and Technology series and is suitable for math majors as well as students and researchers in statistics, computer science, engineering, economics, and finance. Math From Scratch Linear algebra, optimization, probability, graph theory, statistics. ML-Focused Ordering Topics chosen for contemporary machine learning & data analysis. Hands-On Python Companion GitHub notebooks via QR codes and links. Exercises & Solutions End-of-section problems; student solutions online. TitleLinear Algebra, Data Science, and Machine Learning AuthorsJeff Calder & Peter J. Olver PublisherSpringer (UTMT series) Published26 August 2025 · Hardcover LengthApprox. 625 pp SpecialInscribed; two signatures; dated Sept 2025 ISBN978-3-031-93763-7 ConditionVery Good Condition Report VERY GOOD Bears a handwritten presentation inscription and two signatures, dated September 2025 (see the dedicated note above and the photos). Apart from that inscription, the text is clean — no highlighting, no underlining, no reader markings. Binding tight; pages crisp. Cover and page edges show some minor wear. Please see photos for the exact copy offered. Ideal For Data Science & ML Students Applied Math Courses Grad & Advanced Undergrad Researchers & Practitioners Calder / Olver Readers Enlightening Minds Same or Next Business Day Shipping · All Flaws Disclosed · Questions Welcome
