The sixth edition of Strang's phenomenally popular textbook features a more active start and new chapters on optimization and learning from data.
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Gilbert Strang has been teaching Linear Algebra at Massachusetts Institute of Technology (MIT) for over fifty years. His online lectures for MIT's OpenCourseWare have been viewed over ten million times. He is a former President of the Society for Industrial and Applied Mathematics and Chair of the Joint Policy Board for Mathematics. Professor Strang is the author of twelve books.
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Hardcover. Condition: new. Hardcover. Linear algebra now rivals or surpasses calculus in importance for people working in quantitative fields of all kinds: engineers, scientists, economists and business people. Gilbert Strang has taught linear algebra at MIT for more than 50 years and the course he developed has become a model for teaching around the world. His video lectures on MIT OpenCourseWare have been viewed over ten million times and his twelve textbooks are popular with readers worldwide. This sixth edition of Professor Strang's most popular book, Introduction to Linear Algebra, introduces the ideas of independent columns and the rank and column space of a matrix early on for a more active start. Then the book moves directly to the classical topics of linear equations, fundamental subspaces, least squares, eigenvalues and singular values in each case expressing the key idea as a matrix factorization. The final chapters of this edition treat optimization and learning from data: the most active application of linear algebra today. Everything is explained thoroughly in Professor Strang's characteristic clear style. It is sure to delight and inspire the delight and inspire the next generation of learners. Millions of students have learned linear algebra from Gilbert Strang. This new sixth edition of his phenomenally popular textbook takes a more active start, streamlines the core material while retaining the author's characteristic clarity, and features new chapters on the vital modern problems of optimization and learning from data. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Seller Inventory # 9781733146678
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