Think Linear Algebra (2023)
88 points
7 hours ago
| 4 comments
| allendowney.github.io
| HN
staplung
1 hour ago
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Allen Downey (author of the above) has a number of books on computer science-y things. You can buy hardcopies but I think all of them are also just freely available.

Here's a few:

Think Complexity

https://github.com/AllenDowney/ThinkComplexity2

Think DSP

https://github.com/AllenDowney/ThinkDSP

Think Stats

https://github.com/AllenDowney/ThinkStats/

Think Bayes

https://github.com/AllenDowney/ThinkBayes2/

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fn-mote
26 minutes ago
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You missed How to Think Like a Computer Scientist.

Many places on the web. Runestone is probably the most useful like but I’ll leave my favorite classic one below.

http://www.openbookproject.net/thinkcs/python/english3e/

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s-zeng
2 hours ago
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Matrix multiplication introduced before vector addition... the "Linear Algebra Done Right" in me is screaming inside.

That being said, it is definitely cool to have a Jupyter-notebook based set of examples of practical linear algebra

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bsoles
2 hours ago
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And eigenvectors in the first lesson!
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finghin
1 hour ago
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I think at the beginning of learning LA I would have benefited from a more broad introduction to the topic by explaining that it is the algebra of transformations, generally linear transformations, and also the art of quantifying those transformations in meaningful ways.

I would have benefited from some more handwaving in this regard (matrix multiplication, eigenvectors and eigenvalues) and less on the mechanics of the operations, before starting on the basic technicalities. But a “lesson” on these topics on day 0 is too soon

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The_Blade
1 hour ago
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Linear Algebra is dope, as in when we got to apply some mid-level linear to a real business problem and it worked i got high
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bonsai_spool
24 minutes ago
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What was the business problem, broadly? How did you apply linear algebra to it?
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fnord77
1 hour ago
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I got my hands on a stanford Math 55 textbook and tried to do the exercises in numpy.
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