[HN Gopher] Linear Algebra for Data Science
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Linear Algebra for Data Science
Author : Garcia98
Score : 53 points
Date : 2024-07-24 21:07 UTC (1 days ago)
(HTM) web link (kyunghyuncho.me)
(TXT) w3m dump (kyunghyuncho.me)
| bdjsiqoocwk wrote:
| I didn't go to university for CS. Instead I did physics. Because
| of that, learning/remind myself of this stuff was relatively
| easy, and so I did it.
|
| And let me tell you, it didn't actually made me a better data
| scientist/model builder, for the same reason that learning how to
| implement some tree traversal didnt make me a better programmer.
| quibono wrote:
| I think I'd argue with both points actually. Though it also
| depends on the nature of work that you do. I imagine good
| intuition with linear algebra is crucial for novel work. If
| you're implementing a model off an arxiv paper maybe not so
| much.
| fifilura wrote:
| Also remember that you (GP) already acquired that intuition
| in your youth. Most things you learn look trivial in
| retrospect. It may be that you already had some use of that.
|
| And if you had not learned those things you may have started
| worrying what this magic thing you don't know so much about
| is. That can also hinder performance.
|
| (Latd edit since I wanted to add). Another reason it is good
| to know stuff is to be able to dispel co-workers trying to
| bullshit. They are everywhere and I don't think they are
| trying to be mean, it is mostly insecurity. But particularly
| in this field I think people will start throwing buzzwords
| around to confuse and lead you away from what is simple and
| important.
|
| But GPs comment is fine as a thought provoker.
| quibono wrote:
| This seems to be a more hands-on linear algebra intro, starting
| with matrices and building up from there. Note I've not actually
| read the whole thing, just skimmed it.
|
| Something similar worth looking at is:
| https://ocw.mit.edu/courses/18-065-matrix-methods-in-data-an...
| fifilura wrote:
| If I were to teach linear algebra I would stick to the 3D
| graphics approach. Maybe as far as including labs for
| implementing a ray-tracer.
|
| It is just the most fun, intuitive and eye opening application of
| basic linear algebra.
|
| Don't forget the fun!
|
| Data science applications can come later.
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