The Little Learner: A Straight Line to Deep Learning

> The initial preview is a little disappointing because it feels like it does a great job displaying the pedagogical style but not enough to demonstrate the pedagogical value (i.e. whether this resource actually does a good job teaching a complex topic).

This is exactly the concern I had when I saw what it was. I'll definitely keep my eye on it and read the reviews.

The great thing about Scheme is that you can learn it in less than 10 minutes and focus on the ideas.

I would think that the main audience for this books would be people who enjoyed the other books in the authors' "Little" series, which almost all use Scheme, so it wouldn't be something new to learn.

Checking the library the book implements can help: https://github.com/themetaschemer/malt

Some time ago I wrote this: https://notabug.org/ZelphirKaltstahl/guile-ml -- It contains a parallelized decision tree implementation in GNU Guile, a Scheme dialect. There is also https://github.com/lloda/guile-ffi-cblas which at least gives fast matrix multiplication. Example usage I have here: https://notabug.org/ZelphirKaltstahl/guile-math-examples/src...

I don't know what is in the book, but things are possible.

I am looking at the GitHub repo for the Malt library developed in the book https://github.com/themetaschemer/malt. It looks like they use Racket (Scheme) vectors to implement tensors. I experimented with loading Keras simple models into Racket several years ago: the built in math library matrix support was fast enough for my needs so the book software may be both pedagogical and useful for smaller problems.

EDIT: I have not tried the OpenBLAS Racket bindings here (https://github.com/soegaard/sci) but perhaps the low level tensor and tensor ops book code could be optimized,

Have not tries this one (yet) but Racket/base is fine for the previous books.

Yes. At least from the preview.

Very much so.

I think the little learner is the reader rather than the book

i think the little part is the chapter sizes on purpose

What do you think of this comment https://news.ycombinator.com/item?id=34812501

You are the best!

[dead]

I bought "The Reasoned Schemer" as physical book and searched for a way to buy it as a PDF version, but could find it nowhere (also had no problem to pay twice for the book).

The Kindle version of it does not even have fixed table cell width for the layout of the conversation.

German book website buecher.de has "The Little Learner" to preorder as ePUB with Adobe DRM. I don't know, if you can buy digital books on this site outside of Germany. Also notice, that copy-protected digital books on this website are highly unusual; most of the books are with watermark instead, if at all.

I have no clue why a book with pedagogical background and custom layout, has copy-protection and no print-quality PDF version (but instead one with poor layout).

I’m also interested in this. Unfortunately, the other schemer/typer books appear to be available for kindle… so that’s likely the best we’ll get

I didn't find one. However, amazon has a kindle version, which might not be what you're looking for!

Just to piggy back on this. The typesetting seems off kindle and other ebook platforms. Anyone seeing this?

Rated on dollars per hour of brain upgrades, thinking and enjoyment, it doesn’t get better than a good book.

The little schemer is $40 now, reasoned schemer is $30, and the little typer is $38 (about twice as thick as the other two).

I had to think on the little schemer, but grabbed it because my ten year old said that the little typer was "interesting", and I thought he might learn something from it.

Probably should finish working through what I have before getting another, though.

There's also "The Little Typer" and "The Little Prover."

The Little Schemer (formerly LISPer) - Intro to Scheme, or perhaps an introduction to computing with Scheme. Guess it depends on perspective.

The Seasoned Schemer - More on Scheme.

The Reasoned Schemer - Minikanren in Scheme

The Little Prover - Proofs about programs

The Little Typer - Dependent types

The Little MLer - The ML language, not machine learning.

A Little Java - Java

I have the first 5 books, but never got around to finishing Little Prover or Typer (got married and moved that year, probably not the best time to try and start something like that). Definitely like the first three and what I read in those other two.

Smullyan, but those are decades old and not application focused.

Yes, a whole series. Look until the author for more.

'Little..' series books are famous for their pedagogical style: small bit of concepts, presented as a dialogue, making you think at each step, in a well thought out order. It will appeal to anyone who wants to build it out themselves, understand the 'big' ideas in the field. Skim through the second chapter to see how this will be done: they define line function in inverted way where slope and intercept are taken as parameters later. Feels weird but exactly the mental model shift we should be doing when thinking about ML.

Read the preface. A very high praise coming from Guy Steele Jr and Peter Norvig.

At the same time, a warning! Scheme based introductions don't appeal to everyone. Some people feel way out of comfort zone in coding with it (which is sad because it is much simpler). Also, the utilitarian appeal is low: it won't right away see a step change in your Pytorch knowledge or whatever. The appeal of these books is to think deeply about fundamental ideas by implementing them in simplest language without too much help.

In short, YMMV. But if you have a long term view it might help you a lot than sort of currently fashionable trends. (Though I must admit that fast.ai is not just a flavor of the season resources but much better!)

Books in the little series are all about "learning by doing", and teach using the Socratic method (question/answer). Each concept is introduced with small problems that build upon each other. You are forced to get your hands dirty from the beginning, passive learning is not really an option. For most people, I think this helps facilitate a much deeper understanding than just reading a text.

I always had trouble with recursive functions when I was new to programming, and many recommended working through "the little schemer" to solve that problem. It was a tough read for me, but the investment was well worth it and it did for me what it said on the tin. I didn't have nearly as much trouble with recursion after that book, but an unfortunate side effect was developing an affinity for lisps which I haven't yet shaken.

I've read the Little Schemer and based on that, it has a unique style of teaching. Every new concept begins as a fun little question and through a series of more questions expands to a whole concept.

It worked very well for me in learning functional programming and some computational theory ideas.

Worth it.

this series of books has an unusual pedagogical style, with a big "bang for the buck" in terms of building up complex systems from basic steps

there is zero fluff, almost zero narration

the books are basically just input output pairs of "now do this, and now that happens"

they are basically a sort of brain data dump for people who can think with computer code

It's special because it ignores the fact that the rest of the world uses Python for deep learning and it's an easy language for beginners too.

Dan Friedman and the Little X-er series.