Matrix Methods in Data Analysis, Signal Processing, and Machine Learning(ocw.mit.edu)

306 pointsby ericolvor 7 Jahren21 comments

ocw.mit.edu

Matrix Methods in Data Analysis, Signal Processing, and Machine Learning

https://ocw.mit.edu/courses/mathematics/18-065-matrix-methods-in-data-analysis-signal-processing-and-machine-learning-spring-2018/

22 comments

axiom92vor 7 Jahren

Thanks for sharing this. It's based on his new book: https://www.amazon.com/Linear-Algebra-Learning-Gilbert-Stran...

stevesimmonsvor 7 Jahren

Can anyone who has seen the book comment on how good it is?

There are just two reviews on Amazon, one 5* and one 1. The 1 said "The book resembles a set of somewhat incomplete and somewhat disorganized lecture notes prepared by a course instructor as a rough outline of the content of his course."

That put me off buying it. So more data points would be helpful!

nagVenkatvor 7 Jahren

I have the book and I wish I didn’t buy (it’s an expensive book). You need to be already pretty good with Linear algebra and most of the material looked like cliff notes of various linear algebra and continuous optimization topics. I still plan to go through it but mildly disappointed.

mrbonnervor 7 Jahren

Would you recommend to get "Introduction to Linear Algebra, Fifth Edition" by Dr. Strang instead?

nagVenkatvor 7 Jahren

It’s a good book and actually serves as a good intro to this book. For Starngs learning from data book, you also need to know some convex optimization (not the difficult). Good luck!

bakingvor 7 Jahren

I bought this book a couple of weeks ago and I've been waiting eagerly for these lectures to be posted.

AareyBabavor 7 Jahren

Playlist on Youtube https://www.youtube.com/playlist?list=PLUl4u3cNGP63oMNUHXqIU...

yannisvor 7 Jahren

Notable is Alan Edelman's tip using Julia at the 36th lecture.

akulkarnivor 7 Jahren

18.06 Linear Algebra was a fun class. Can’t believe he is still teaching.

charlyslvor 7 Jahren

Labs, although mentioned in the syllabus, are not in the OCW materials. This is the best I could find (4 labs in Julia, Julia notebooks, and Matlab): https://github.com/dkout/18.065

pixelperfectvor 7 Jahren

Thanks for sharing. I hope at age 83 I can be as mentally sharp as Gilbert Strang is.

axiom92vor 7 Jahren

Depending on how old you are now, by the time you're 83, you could find yourself being a part of the new "middle aged" group :-) (i.e., we could end up inventing ways of increasing our lifespan dramatically).

adamisomvor 7 Jahren

or there could be nobody around to make the observation that there's nobody around, if any existential risks actualize

usgroupvor 7 Jahren

You’re doing SVD by lecture 3 (typically the last thing you do on a LA II course), so brace yourself. If you’re not already VERY good at LA I’d wait until you are before attempting this.

anilakarvor 7 Jahren

Not trying to mock anyone, but linear algebra is basic university level math.

vonmoltkevor 7 Jahren

If you had the course. It was not in the engineering curriculum at my university. We got four semesters (effectively) of calculus instead.

aj7vor 7 Jahren

Looks like state variables and signal processing, now mature with LabView and MatLab plugins and standard VLSI solutions being deemphasized in favor of machine learning and data science.

AceJohnny2vor 7 Jahren

Ooh this is interesting. His Linear Algebra book was my favorite source on the topic back in college (though I hear people have alternate preferences).

shstalwartvor 7 Jahren

I really like Axler's Linear Algebra Done Right. It's all conceptual (i.e., proofs), and doesn't focus on computation at all.

bigred100vor 7 Jahren

Thank you OP. This looks like a wonderful resource.

jay754vor 7 Jahren

Seems like an awesome course. Thanks for sharing

sara7262vor 7 Jahren