Here's a preview of the first two chapters: https://mitpress.ublish.com/ebook/the-little-learner-a-strai...
Given the wealth of information and the problem of appraising it all, I don't think it helps this book that it costs $55 and requires the reader to learn an esoteric language (for the field), when there are so many educational books and lecture series by experts in the field that you can find freely available online.
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.
> Maybe, maybe not. But even if you use a machine learning toolkit like TensorFlow or PyTorch, what you will take away from this book is an appreciation for how the fundamentals work.
So yep, must have. If you haven’t read the rest, they are really must haves imho.
EDIT: Half Life 3 confirmed: "Presents key ideas of machine learning using a small, manageable subset of the Scheme language"
I don't know what is in the book, but things are possible.
(trivia, he's also behind djvu format)
I think with a little of patience I can get by.
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,
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).
Have to think about this for a while :)
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.
https://mitpress.mit.edu/9780262561150/a-little-java-a-few-p...
I like the style of these books, and might read this one - I'm just worried that Java has changed quite a bit since then. Is it still, say, 90% OK?
I know _why wrote his books as a conversation between two foxes.
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.
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!)
My criticism with fast.ai, (I am part time educator), is that this approach is an information overload and poor sequencing. Their comparison with Teach whole game approach is flawed because a game of, say Football, is essentially simple. So you can say just start kicking around. But we don't teach chess this way. It is accepted that you have to spend some time upfront to learn the rules before you can play even simple game. Sure one need not learn castling or en-passant upfront. But you get the drift.
This book (looking at the preview chapters) is going to follow the lego blocks approach or bottoms up approach to build it. For me, this is correct way to teach supervised ML focussed on neural networks and deep learning. We have a problem of too many library plumbers in the ML field currently. People who can piece together library function calls without knowing why it is working. But this house of cards is not sustainable strategy to build AI based application over long term.
Long story short, the book will need patience but that patience will be worth it!
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.
Too little of that in this world nowadays. Too much ios and not enough arch linux.
If you have never used lisp, you need to be patient with the notation and resist the urge to balk at what is unfamiliar. I remember grumbling quite a bit when I first went through TLS, but that phase was over pretty quickly and within days I had no trouble following the code.
Are there better ways to introduce deep learning and neural networks? Maybe.. but I like "little" books and there is no better way to learn something than by building it yourself. For that reason alone I'd recommend the book sight unseen (but with the knowledge of prior little books). I do think choosing what is likely an unfamiliar language for most may be somewhat of an impediment for an already challenging topic, but scheme is a simple language and allows the author to focus on the ML concepts.
I'm highly confident you'll learn a lot, if you put in the work. For DL as a separate topic, the best resources I've found are:
- 3 blue 1 brown Neural Net playlist
- Karpathy's "The spelled-out intro to neural networks and backpropagation"It worked very well for me in learning functional programming and some computational theory ideas.
Worth it.
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
In particular, Scheme. If your language of choice is, say, Python, then you'll want to get a primer on Scheme before reading this particular book. Maybe by starting at the beginning of the series.