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There is good reason to be excited about Linear Algebra. With the world becoming increasingly digital, Linear Algebra is gaining more and more importance. When we send texts, share video, do internet searches, there are Linear Algebra algorithms in the background that make it work.

This concise introduction to Linear Algebra is authored by a leading researcher presents a book that covers all the requisite material for a first course on the topic in a more practical way.

The book focuses on the development of the mathematical theory and presents many applications to assist instructors and students to master the material and apply it to their areas of interest, whether it be to further their studies in mathematics, science, engineering, statistics, economics, or other disciplines.

Linear Algebra has very appealing features:
•It is a solid axiomatic based mathematical theory that is accessible to a large variety of students.
•It has a multitude of applications from many different fields, ranging from traditional science and engineering applications to more ‘daily life’ applications.
•It easily allows for numerical experimentation through the use of a variety of readily available software (both commercial and open source).

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Frequently bought with Data Science and Machine Learning: Mathematical and Statistical Methods (Chapman & Hall/Crc Machine Learning & Pattern Recognition)


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