4 ms·

I wish there was a Missing Semester of Linear Algebra course to help people go from "Okay I have a course or two in linear algebra, I know what span, vectors, b

by csense 4y ago

I wish there was a Missing Semester of Linear Algebra course to help people go from "Okay I have a course or two in linear algebra, I know what span, vectors, basis and dimension mean, the formal definition of an inner product space, and I can do Gauss-Jordan elimination, determinants and eigenvalues for small matrices with paper and pencil" to "I have a 100x100 matrix of noisy data from sensors and this research paper I found tells me I can do some fantastic stuff if I compute such-and-such involving eigenvalues or inverses or whatnot. Or maybe I have a process with 1000 states where I know the probability objects move from state i to state j for each pair (i, j) and I want to find the steady state. How do I wrangle numpy into doing what I need?" MIT has a course called The Missing Semester of Your CS Education [1]. It tells you about practical stuff that you need to know but isn't really taught in classes (shells, version control, build systems, package managers, VM's). There needs to be something similar for linear algebra, it seems like there's a lot of folk knowledge and a big gap between what typical undergrad courses train you to do and what you encounter in actual practical problems. (And don't get me started on all the weird linear algebra stuff they have going on in e.g. quantum physics.) [1] https://missing.csail.mit.edu/about/ https://missing.csail.mit.edu/about/

cschmid 4y ago
I don't exactly know what you mean, but at least most points in the blog post were covered in my undergrad numerics courses.
bernulli 4y ago
Sounds like a vanilla numerical math course?
- Q6T46nT668w6i3m 4y ago
  I don’t know your age but I expect you’re a bit older! This has changed dramatically in the past 20-30 years and has been a contentious issue for the past few in the computer science education community. Many programs, if they even offer numerical analysis coursework, provide it to supplement regular analysis coursework (rather than computer science coursework).
  - bernulli 4y ago
    Maybe ;-) I do know that this course is still offered widely across the US, but maybe not within CS, and maybe not as a mandatory course. But, bottom line: if you're interested, it's very likely you can take it - you may have to check your school of engineering or applied math department.
  - Mimmy 4y ago
    Do you have any more context on the contentiousness of including numerical analysis in a traditional cs curriculum? I’m curious to know what the arguments are on both sides. I’ve also recently noticed that programs and students outside North America seem to take the content much more seriously.
    - eru 4y ago
      I had a computer numerics course even for studying pure mathematics. That was in Germany in the early 2000s.
tomrod 4y ago
It's a master degree course called Matrix Analysis (e.g Horn and Johnson as text).
- hintymad 4y ago
  Would the libraries take care of most of the algorithms mentioned in Horn's book? I was wondering if there's something in between: it goes beyond basic linear algebra, but it uses the numerical libraries to process the large matrices to solve complex problems.
- vicnov 4y ago
  Is it close to 18.065 from Prof Strang?
chrsig 4y ago
check out prof. steve brunton’s youtube channel[0] — it’s light on the numpy side of things, but he’s got a lot of material going from first principles to dealing with huge matrices, compressed sensing, dynamical systems, ML, etc [0] https://www.youtube.com/c/Eigensteve https://www.youtube.com/c/Eigensteve
aoki 4y ago
Sounds like EE263 at Stanford. Stephen Boyd’s lectures are on YouTube and so are most of the slides and psets. https://ee263.stanford.edu/archive/ https://ee263.stanford.edu/archive/
stiff 4y ago
Stanford has ENGR108 [1] based on freely available book "Introduction to Applied Linear Algebra – Vectors, Matrices, and Least Squares" [2] by Stephen Boyd, with video lectures [3] available. EE263 [4] is sort of a continuation of this at a more advaneced level, it originally also was developed by Boyd and also has video lectures available [5] [1] https://stanford.edu/class/engr108/ https://stanford.edu/class/engr108/ [2] https://web.stanford.edu/~boyd/vmls/ https://web.stanford.edu/~boyd/vmls/ [3] https://www.youtube.com/watch?v=oR6G1MUMveE https://www.youtube.com/watch?v=oR6G1MUMveE [4] https://ee263.stanford.edu/ https://ee263.stanford.edu/ [5] https://www.youtube.com/playlist?list=PL06960BA52D0DB32B https://www.youtube.com/playlist?list=PL06960BA52D0DB32B

by csense 4y ago

cschmid 4y ago

I don't exactly know what you mean, but at least most points in the blog post were covered in my undergrad numerics courses.

bernulli 4y ago

Sounds like a vanilla numerical math course?

Q6T46nT668w6i3m 4y ago
I don’t know your age but I expect you’re a bit older! This has changed dramatically in the past 20-30 years and has been a contentious issue for the past few in the computer science education community. Many programs, if they even offer numerical analysis coursework, provide it to supplement regular analysis coursework (rather than computer science coursework).
- bernulli 4y ago
  Maybe ;-) I do know that this course is still offered widely across the US, but maybe not within CS, and maybe not as a mandatory course. But, bottom line: if you're interested, it's very likely you can take it - you may have to check your school of engineering or applied math department.
- Mimmy 4y ago
  Do you have any more context on the contentiousness of including numerical analysis in a traditional cs curriculum? I’m curious to know what the arguments are on both sides. I’ve also recently noticed that programs and students outside North America seem to take the content much more seriously.
  - eru 4y ago
    I had a computer numerics course even for studying pure mathematics. That was in Germany in the early 2000s.

tomrod 4y ago

It's a master degree course called Matrix Analysis (e.g Horn and Johnson as text).

hintymad 4y ago
Would the libraries take care of most of the algorithms mentioned in Horn's book? I was wondering if there's something in between: it goes beyond basic linear algebra, but it uses the numerical libraries to process the large matrices to solve complex problems.
vicnov 4y ago
Is it close to 18.065 from Prof Strang?

chrsig 4y ago

check out prof. steve brunton’s youtube channel[0] — it’s light on the numpy side of things, but he’s got a lot of material going from first principles to dealing with huge matrices, compressed sensing, dynamical systems, ML, etc [0] https://www.youtube.com/c/Eigensteve https://www.youtube.com/c/Eigensteve

aoki 4y ago

Sounds like EE263 at Stanford. Stephen Boyd’s lectures are on YouTube and so are most of the slides and psets. https://ee263.stanford.edu/archive/ https://ee263.stanford.edu/archive/

stiff 4y ago

Stanford has ENGR108 [1] based on freely available book "Introduction to Applied Linear Algebra – Vectors, Matrices, and Least Squares" [2] by Stephen Boyd, with video lectures [3] available. EE263 [4] is sort of a continuation of this at a more advaneced level, it originally also was developed by Boyd and also has video lectures available [5] [1] https://stanford.edu/class/engr108/ https://stanford.edu/class/engr108/ [2] https://web.stanford.edu/~boyd/vmls/ https://web.stanford.edu/~boyd/vmls/ [3] https://www.youtube.com/watch?v=oR6G1MUMveE https://www.youtube.com/watch?v=oR6G1MUMveE [4] https://ee263.stanford.edu/ https://ee263.stanford.edu/ [5] https://www.youtube.com/playlist?list=PL06960BA52D0DB32B https://www.youtube.com/playlist?list=PL06960BA52D0DB32B