Good reading on Applied Linear Algebra?

In summary, I'd like to see more books/reading on the applications of abstract Linear Algebra to other fields of Math, or physics.
  • #1
CSteiner
31
0
I've been studying graduate level Linear Algebra from Steven Roman's Advanced Linear Algebra (Springer, GTM). It is a terrific book, but many of the concepts are extremely abstract so that I find it difficult to retain what I've learned. Can anyone point me to some books/reading on the applications of abstract Linear Algebra to other fields of Math, or physics? Note that I am not referring to the low level matrix manipulation approach taught in undergrad, but the more heavy ideas. For a feel of what I'm dealing with, here is the table of contents:

1.Vector Spaces
2. Linear Transformations
3.The Isomorphism Theorems
4.Modules I:Basic Properties
5. Modules II: Free and Noetherian Modules
6. Modules over a Principle ideal Domain
7. The Structure of a Linear Operator
8. Eigenvalues and Eigenvectors
9. Real and Complex innerprodict spaces
10. Structure Theory for Normal Operators.
 
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  • #2
CSteiner said:
For a feel of what I'm dealing with, here is the table of contents:
This is part of the table of contents, correct? Are these the subjects that you would particularly like to see applications of?

I have more than once contemplated buying and studying (parts of) this book. So far I have decided against it because it is a bit too algebraic for me and (as you also remarked) it seems to lack applications, but maybe I will change my mind.

Would Matrices: Algebra, Analysis and Applications by S. Friedland be something for you, or is that too much towards matrix theory for your tastes?
 
  • #3
Krylov said:
This is part of the table of contents, correct? Are these the subjects that you would particularly like to see applications of?

Yes, this is the first half of the book, and these are the subjects I'd like to see some examples of.

Krylov said:
Would Matrices: Algebra, Analysis and Applications by S. Friedland be something for you, or is that too much towards matrix theory for your tastes?

I may try this, the applications to graph theory look promising. To be honest though, this seems more like an equivalently abstract formulation of the subject in terms of matrices. I'm more looking for specific instances of the concepts in physics and other areas of math.
 

1. What is the purpose of studying Applied Linear Algebra?

Applied Linear Algebra is used to solve real-world problems by modeling them mathematically and using linear algebra techniques to analyze and find solutions. It is a valuable tool for various fields such as engineering, computer science, economics, and physics.

2. What are some key concepts in Applied Linear Algebra?

Some key concepts in Applied Linear Algebra include vector spaces, matrices, systems of linear equations, eigenvalues and eigenvectors, and least squares regression. These concepts are used to represent and manipulate data, solve systems of equations, and make predictions.

3. How is Applied Linear Algebra used in machine learning?

Applied Linear Algebra plays a crucial role in machine learning. It is used to create and train models, make predictions, and analyze the performance of machine learning algorithms. Techniques such as principal component analysis and singular value decomposition are commonly used in machine learning applications.

4. Can you give an example of a real-world application of Applied Linear Algebra?

One example of a real-world application of Applied Linear Algebra is Google's PageRank algorithm, which is used to rank web pages in search results. This algorithm uses matrix operations to determine the importance of a web page based on the links it has to other pages.

5. What are some resources for learning more about Applied Linear Algebra?

Some resources for learning more about Applied Linear Algebra include textbooks such as "Introduction to Linear Algebra" by Gilbert Strang and online courses such as "Applied Linear Algebra" on Coursera. Additionally, there are many online tutorials, practice problems, and forums available for self-paced learning and further exploration of the subject.

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