
Matrix Methods in Data Analysis, Signal Processing, and Machine Learning - ericol
https://ocw.mit.edu/courses/mathematics/18-065-matrix-methods-in-data-analysis-signal-processing-and-machine-learning-spring-2018/
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axiom92
Thanks for sharing this. It's based on his new book:
[https://www.amazon.com/Linear-Algebra-Learning-Gilbert-
Stran...](https://www.amazon.com/Linear-Algebra-Learning-Gilbert-
Strang/dp/0692196382/)

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stevesimmons
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!

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nagVenkat
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.

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

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nagVenkat
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!

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AareyBaba
Playlist on Youtube
[https://www.youtube.com/playlist?list=PLUl4u3cNGP63oMNUHXqIU...](https://www.youtube.com/playlist?list=PLUl4u3cNGP63oMNUHXqIUcrkS2PivhN3k)

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

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

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charlysl
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](https://github.com/dkout/18.065)

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

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axiom92
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).

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

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usgroup
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.

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

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

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aj7
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.

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AceJohnny2
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).

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

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bigred100
Thank you OP. This looks like a wonderful resource.

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jay754
Seems like an awesome course. Thanks for sharing

