Need calculus and several books as a prerequisite for Machine Learning

AI Thread Summary
The discussion centers around seeking resources for learning advanced mathematical concepts essential for machine learning, specifically Lagrangian multipliers, duality, matrix calculus, eigenvalues, and eigenvectors. The user has a solid foundation in Calculus and Linear Algebra but is looking to enhance their knowledge in these new areas. Recommendations for self-study materials include free online books, particularly one by Kenneth Kuttler for calculus and optimization topics, as well as resources from e-booksdirectory.com. Additional suggestions include exploring courses on Convex Optimization available on YouTube and a tutorial site for Calculus and Linear Algebra. The conversation emphasizes the importance of finding accessible educational materials to facilitate learning in these complex subjects.
njama
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Hey!

Happy New Year 2013 to all of you!

I am in good mood for learning something new so I need advice.

I'm currently watching the videos for Machine learning from Stanford University, but I'm stuck at Lagrangian multipliers and duality.

I got solid background in Calculus I and II (I read and learned from the book by Irl Bivens and I really like it) but I've never learned about Lagrange multipliers nor Matrix Calculus, and now it's time to step my Calculus up :smile:

Also I got solid basic background in Linear Algebra but never learned about Eigenvalues and Eigenvectors or Semidefinite Matrices.

So I need some book for self-studying:

Here are the topics that are new to me:

Matrix Calculus 20
4.1 The Gradient . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20
4.2 The Hessian . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22
4.3 Gradients and Hessians of Quadratic and Linear Functions . . . . . . . . . . 23
4.4 Least Squares . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25
4.5 Gradients of the Determinant . . . . . . . . . . . . . . . . . . . . . . . . . . 25
4.6 Eigenvalues as Optimization

3.10 The Determinant . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14
3.11 Quadratic Forms and Positive Semidefinite Matrices . . . . . . . . . . . . . . 17
3.12 Eigenvalues and Eigenvectors . . . . . . . . . . . . . . . . . . . . . . . . . . 18
3.13 Eigenvalues and Eigenvectors of Symmetric Matrices . . . . . . . . . . . . . 19

Convex Optimization
Convex Optimization Part 2

Here are the materials from the course (there are documents in Section Notes).

Thanks a lot.

Regards.
 
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I would first look at free books online.

FOr calculus, including Hessians and basic optimization, one nice option is the book by Kenneth Kuttler to be found at:
http://www.e-booksdirectory.com/listing.php?category=4

Other books in this category may fit the bill for Hessians as well, so browse around and see what works for you. This book also covers eigenvectors and such.

Other linear algebra references can be found:
http://www.e-booksdirectory.com/listing.php?category=538
I like the books by Heffron listed there (you can buy a hardcopy via amazon for <$20 US), as well as the book "linear algebra done wrong" by Treil (which is harder than Heffron).

Again, browse around. Good luck!

jason
 
Thanks a lot for the help, I have never heard about e-booksdirectory.com it's pretty cool site for free e-books.

I've found courses from Stanford on Youtube about Convex Optimization and some applied linear algebra.

Regards.
 
For the following four books, has anyone used them in a course or for self study? Compiler Construction Principles and Practice 1st Edition by Kenneth C Louden Programming Languages Principles and Practices 3rd Edition by Kenneth C Louden, and Kenneth A Lambert Programming Languages 2nd Edition by Allen B Tucker, Robert E Noonan Concepts of Programming Languages 9th Edition by Robert W Sebesta If yes to either, can you share your opinions about your personal experience using them. I...
This is part 2 of my thread Collection of Free Online Math Books and Lecture Notes Here, we will consider physics and mathematical methods for physics resources. Now, this is a work in progress. Please feel free comment regarding items you want to be included, or if a link is broken etc. Note: I will not post links to other collections, each link will point you to a single item. :book:📚📒 [FONT=trebuchet ms]Introductory college/university physics College Physics, Openstax...

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