
Numerical Linear Algebra for Programmers - dragandj
https://aiprobook.com/numerical-linear-algebra-for-programmers?release=0.9.0
======
arcturus17
I have to echo what others have said: great book idea, but not so hot on the
model.

I studied linear algebra in college and I could use a refresher for AI, but I
don’t want to study math in the traditional way, with convoluted abstract
examples that lead nowhere. Hated it back then and hate it now. The prospect
of doing it in code makes it infinitely more exciting so you’ve definitely got
something going on there there...

However, I’m not going to get into _another_ subscription, mainly because I
don’t want to check every month to see the state of the project.

I’d personally pay you around $40 for an early access fee that also gets me
the final product... It’d be a discount from your target price but I’d also be
taking a risk (what if you don’t finish it?).

I’m favoriting this and will check how it evolves. Worst case, I’ll buy the
finished product if the reviews are good!

~~~
arto
You may be looking for this book: [https://www.manning.com/books/math-for-
programmers](https://www.manning.com/books/math-for-programmers)

~~~
arcturus17
That looks great, thank you. I’m actually tempted to buy it - have you worked
through it?

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dragandj
Part of my Interactive Programming for Artificial Intelligence book series.

The companion book in the same series:

Deep Learning for Programmers: An Interactive Tutorial with CUDA, OpenCL,
DNNL, Java, and Clojure

[https://aiprobook.com/deep-learning-for-
programmers/](https://aiprobook.com/deep-learning-for-programmers/)

------
Already__Taken
I saw a great talk explaining linear algebra where the presenter used it to
solve the angles of an arm joint to place an animated robot arm at a specific
co-ordinate.

I think it might be this actually, can't watch it all right now to check. Demo
I'm thinking of should be
[https://youtu.be/3v75aX5-gSA?t=1436](https://youtu.be/3v75aX5-gSA?t=1436)

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the_svd_doctor
For a great introduction to numerical linear algebra, I cannot recommend
enough the book from Trefethen and Bau.

Or Golub & Van Loan, if you like pain.

~~~
nextos
I don't like Strang books that much as I find them a bit verbose, but his
latest one is geared towards machine learning and it's pretty good:
[http://math.mit.edu/%7Egs/learningfromdata/dsla_toc.pdf](http://math.mit.edu/%7Egs/learningfromdata/dsla_toc.pdf)

He covers some numerical linear algebra, and he spends a lot of time on topic
modeling and deep learning.

~~~
enriquto
> I don't like Strang books that much as I find them a bit verbose

I'm not sure I agree with you. I remember his elementary calculus book, where
he states and proves the fundamental theorem of calculus on the first two
pages (including the definition of derivative and the definition of integral).
He says something like "this is not a car analogy, this is the real thing and
we are already done, the rest of the book is just minor details and examples".
I do not know how you can be more concise than this, considering that half of
the first page was taken by a cute drawing of a speedometer and an odometer.
That you call verbose?

~~~
signa11
two different books, just like people, can have two different styles right ?

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bhattisatish
The book looks interesting and the associated libraries (neanderthal for e.g.)

But while going through your performance comparison [1], I feel something is
off.

I am not that familiar with libpython-clj and how it works, but looks like you
are loading python from within the JVM and in turn the python is loading the
C++/fortran OpenBLAS libraries to get the numerical calculations done for the
Correlation Coefficient. I suspect this multi-level indirection is creating
it's own performance overhead. For now, I don't believe the performance
benchmark are telling us the true story :-)

But after saying all that, I love how concise is the clojure implementation
is.

[1] [https://dragan.rocks/articles/20/Clojure-Numpy-Cupy-CPU-
GPU](https://dragan.rocks/articles/20/Clojure-Numpy-Cupy-CPU-GPU)

~~~
gandreani
The follow up article addresses this concern. Similar results

[https://dragan.rocks/articles/20/Clojure-Numpy-Cupy-CPU-
GPU-...](https://dragan.rocks/articles/20/Clojure-Numpy-Cupy-CPU-GPU-2)

~~~
scottlocklin
Yeah, well, that's a nonsense comparison: the neanderthal package is freaking
lapack (in C++), and they used a java trick to get Clojure fast on it
(basically run the C++ on allocated unmanaged memory blobs, which is the only
marginally sane thing one can do in a language like Clojure). I wrote an early
version of this in Clojure before throwing my hands up at the atrocity of
doing this sort of thing. They also wash over very obvious (to anyone who
knows how a computer works) issues with using Cuda and Clojure numerics in
general. Misleading and Fail statements.

If the whole book is filled with such chirpy and wrong assertions, they should
fall on their swords for offending their numeric linear algebra forefathers
and the shame of it all.

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culopatin
Now even books are subscriptions?!

~~~
dragandj
Author here.

Please consider an alternative viewpoint: you can try the book draft for $9,
and if you don't like it, just don't continue subscription. Total cost: $9.

If you like the book, please consider that 100% of the book proceeds go
towards the development of related _free open source libraries_
[https://github.com/uncomplicate](https://github.com/uncomplicate)

~~~
KallDrexx
I've bought plenty of MEAP books at Manning that were incomplete. The
difference is that I only had to pay the $30-40 (normal book price) one time
and never think about it again, and new revisions would just be delivered to
me.

There have been several early access books where the author needed to take a
(well deserved) break, or be slow at delivering new chapters because of other
revisionary work. This has sometimes meant a few months without new content,
which I was OK with in that model.

In this model I could easily end up spending way more than than that, and
every month I have to make a decision if it's worth cancelling.

Not only that you have another book on there that's "early access too" so you
are juggling two books (and books are not trivial things to write and get
finished/polished). So how am I to expect you'll get either done in a
reasonable time.

So sorry, I'd be happy to give you a flat $30 for early access to the book and
full access to the ebook when it's finished, but I'm not going to subscribe
and hope it's in a good state prior to reaching that point in monthly fee.

This is despite I think this book is very much what I'm looking for as I'm
wanting to get into 3d graphics, but I'll pass.

~~~
iamcreasy
I've bought early access book from Manning as well, and after few months of
silence the author decided to drop the chapters that I was looking forward.
Left a bad taste in my mouth.

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ramosu
No way..

After backing and not receiving Punk Mathematics since 2010, I realized paying
for something unfinished makes absolutely no sense at all.

I prefer to pay more and get something complete.

~~~
dragandj
Just to clarify: the book you backed and got burned with in 2010 has no
relation to this author nor this book.

~~~
Insanity
Good comment, my initial thought after reading the parent was that it was by
the same person.

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benstrumental
> no C++ build hell

> no C++ syntax hell!

> no C++ at all!!!

The author of this book has some strong feelings about C++.

~~~
orange3xchicken
The two classic graduate texts for numerical linear algebra are Matrix
Computations by Golub and Van Loan and Numerical Linear Algebra by Trefethen
and Bau.

The reference you are looking for (includes executable C++) is Numerical
Recipes by William Press et al.

There are a couple other good ones as well that are more broad - e.g.
Quarteroni, Sacco, & Saleri Numerical Mathematics also covers numerical
diffeq, convex geometry, & approximation theory.

I can't comment on how OP's book fits in.

~~~
scottlocklin
Trefethen&Bau, Golub & Van Loan and Demmel's "Applied Numerical Linear
Algebra" make up the holy trinity. I don't know what audience the OP book is
supposed to serve, but it's evident on inspection; it ain't me.

~~~
orange3xchicken
The best thing I remember from Demmel's book is that i'm pretty sure the
spooky possessed baby on the cover is his kid.

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floatingatoll
My interpretation of this subscription landing page was that I could preview a
few pages from the book to see if the writing style worked for me. I wasn't
able to figure out how to do so, as the 'AVAILABLE' link next to the linear
algebra refresher simply went to a Patreon page full of locked/unavailable
posts. This looks like it could be nifty, but the ultra-polished marketing is
too focused on paid conversions and doesn't meet the basic necessaries of "Is
this content valuable to me?".

~~~
dragandj
[https://dragan.rocks](https://dragan.rocks)

and also the Downloads section of the
[https://aiprobook.com](https://aiprobook.com)

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augustt
Does this include "traditional" numerical linear algebra (e.g. stability,
conditioning) or is it the modern deep learning interpretation that linear
algebra ≈ matrix multiplication?

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sabas123
Is there some sort of preview material? I am always quite skeptical about
mathematics through programming books, so it would be nice to get a feel for
it's rigor.

~~~
99_00
[https://aiprobook.com/downloads/lafp-sample-vector-
spaces-0....](https://aiprobook.com/downloads/lafp-sample-vector-
spaces-0.1.0.pdf)

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smoyer
I think there's a misspelling on your pitch page - "aren’t these two frends
adorable? the book is too!"

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mkagenius
I am trying to read Axler's book and it is proving to be extremely boring to
me (no offense to the author) but this post gave me an idea that I should
probably explore a linear algebra library along with the book to make things
interesting.

~~~
enriquto
I also find Axler unbearable. If you are interested specifically in matrices,
the book by Denis Serre is quite a masterpiece. And if you are interested in
numerical linear algebra, the book by Tim Davis "Direct Methods for Sparse
Linear Solvers" is also extremely beautiful and readable (the goal is not the
software implementation in itself, but most of the presented algorithms are
illustrated by pseudocode, and some of them even in C).

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deltasquared
It lost me at no C++ at all.

