And The Rest Is Just Algebra
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And the Rest is Just Algebra
This book addresses college students' weak foundation in algebra, its causes, and potential solutions to improve their long-term success and understanding in mathematics as a whole. The authors, who are experts in a wide variety of fields, emphasize that these difficulties are more complex than just forgotten rules, and offer strategic approaches from a number of angles that will increase the chances of student understanding. Instructors who are frustrated with their students’ lack of skills and knowledge at college level will find this volume helpful, as the authors confront the deeper reasons why students have difficulties with Algebra and reveal how to remedy the issue.
And the Rest is Just Algebra
This book addresses college students' weak foundation in algebra, its causes, and potential solutions to improve their long-term success and understanding in mathematics as a whole. The authors, who are experts in a wide variety of fields, emphasize that these difficulties are more complex than just forgotten rules, and offer strategic approaches from a number of angles that will increase the chances of student understanding. Instructors who are frustrated with their students’ lack of skills and knowledge at college level will find this volume helpful, as the authors confront the deeper reasons why students have difficulties with Algebra and reveal how to remedy the issue.
Linear Algebra for Everyone
Author: Gilbert Strang
language: en
Publisher: Wellesley-Cambridge Press
Release Date: 2020-11-26
Linear algebra has become the subject to know for people in quantitative disciplines of all kinds. No longer the exclusive domain of mathematicians and engineers, it is now used everywhere there is data and everybody who works with data needs to know more. This new book from Professor Gilbert Strang, author of the acclaimed Introduction to Linear Algebra, now in its fifth edition, makes linear algebra accessible to everybody, not just those with a strong background in mathematics. It takes a more active start, beginning by finding independent columns of small matrices, leading to the key concepts of linear combinations and rank and column space. From there it passes on to the classical topics of solving linear equations, orthogonality, linear transformations and subspaces, all clearly explained with many examples and exercises. The last major topics are eigenvalues and the important singular value decomposition, illustrated with applications to differential equations and image compression. A final optional chapter explores the ideas behind deep learning.