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The Little Learner: A Straight Line to Deep Learning

mitpress.mit.edu

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Re: The Little Learner: A Straight Line to Deep Learning

#31

Post by bzhang255 »

sn9 wrote: post #28
bzhang255 wrote: post #26

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). 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 l…

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

Sure - but I think that's the least important part of my comment. The preview is basically just an intro to Scheme. I would rather be able to see how well the book covers interesting ideas about deep learning. While the jury is still out, my personal skepticism is that this is a really beautiful passion project that looks great on bookshelves, but that any serious learner would be better served dedicating their time to working through the existing, more traditional, and very high-quality resources available online.

Re: The Little Learner: A Straight Line to Deep Learning

#32

Post by timmg »

bzhang255 wrote: post #26

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). 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 l…

> 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.

Re: The Little Learner: A Straight Line to Deep Learning

#33

Post by leoc »

drcode wrote: post #17
boredemployee wrote: post #10

Why is this book so special, could someone enlighten me?

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

Guy Steele's keynote talk at Dan Friedman's 60th-birthday academic festival, "Dan Friedman--Cool Ideas", gives lots of the background: https://youtu.be/IHP7P_HlcBk?t=2198 . Apparently the format was originally a parody or adaptation of that of an IBM Fortran instruction manual based on Skinnerian programmed-instruction ideas.

Re: The Little Learner: A Straight Line to Deep Learning

#36

Post by zelphirkalt »

bzhang255 wrote: post #31
sn9 wrote: post #28

Earlier quoted context omitted.

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

Sure - but I think that's the least important part of my comment. The preview is basically just an intro to Scheme. I would rather be able to see how well the book covers interesting ideas about deep learning. While the jury is still out, my personal skepticism is that this is a really beautiful passion project that looks great on bookshelves, but that any serious learner would be better served dedicating their time…

This is what the book has to say (part of a foreword by Peter Norvig):

> 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.

Re: The Little Learner: A Straight Line to Deep Learning

#38

Post by solaxun »

boredemployee wrote: post #23
solaxun wrote: post #18

Earlier quoted context omitted.

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…

ok cool! thanks for explaining. do you think a beginner in the world of AI and programming would benefit from this DL book as well?

Tough to answer since I've only read the two intro chapters currently available. I'm still in the early stages myself with with Deep Learning but have years of experience with programming and lisp, so I'm coming in with a background that might bias my views.

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"

Re: The Little Learner: A Straight Line to Deep Learning

#40

Post by pbk1 »

tejtm wrote: post #37
bigdict wrote: post #19

No way. Does it use Scheme? EDIT: Half Life 3 confirmed: "Presents key ideas of machine learning using a small, manageable subset of the Scheme language"

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

IIRC you can use Racket base so long as you define the “atom” function per the book authors
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