8 ms·
The Little Book of Deep Learning [pdf]
- ksd482 3y agoBy "little" I thought it would be brief, which I think it sort of is. But what it really means by little is that it is optimized for little screens such as a smartphone. Go ahead and open it in your phone. You'll be delighted to read it. Question for HN: how can I convert my existing PDFs and eBooks that I can easily read from my phone? For e.g., I have a lot of Math textbooks in PDF format and I would like to convert them into a format similar to this deep learning book. How can I go about doing that?
- MacTea 3y agoReads great on Kindle too! To answer your question: Calibre might be able to help you out!
- sthatipamala 3y agoLook into k2pdfopt. The term you’re looking for is you want to “reflow” your PDFs
- lnyan 3y agohttps://github.com/koreader/koreader https://github.com/koreader/koreader koreader has a pdf reflow mode
- wodenokoto 3y agoYour comment prompted me to look around. There is also an A5 version of the book https://fleuret.org/public/lbdl-a5-booklet.pdf https://fleuret.org/public/lbdl-a5-booklet.pdf Which again, is a small paper size!
- driscoll42 3y agoGood find! Though the inversion of every other page makes it difficult to read unless printing out
- totetsu 3y agoCareful not to swallow this.
- abhayhegde 3y agoWhat a neat little book! I suppose this was typeset in TeX. How did they optimize for smaller width though? Edit: I found the style templates on author's webpage [1]. [1]: https://fleuret.org/cgi-bin/gitweb/gitweb.cgi?p=littlebook.git;a=summary https://fleuret.org/cgi-bin/gitweb/gitweb.cgi?p=littlebook.g...
- abhayhegde 3y agoIf you have texlive-extra installed, this mobile-friendly PDF can be converted to a desktop-readable format using: pdfxup -o lbdla4.pdf -ow -im 10 -m 40 -is 0 -fw 0 --portrait -nup 2x2 lbdl.pdf
- lamontcg 3y agoAre there arguments to that to tile it by columns first instead of rows? (but not one long column all the way down the left to the end and then one long column on the right, just want to shuffle the order on each page). It reads kind of r/nosafetysmokingfirst to me. (And its `brew install texlive` on mac to get pdfxup for anyone else wondering)
- hota_mazi 3y agoI know La/TeX is the standard for this but I'm still irritated that it forces all diagrams to appear at the top of the page, which really gets in the way of explaining things clearly. This books suffers a lot from this limitation, with figures sometimes appearing 5 pages before they are actually referenced in the text.
- abhayhegde 3y agoI am not sure if that is entirely correct. For e.g., see p.no. 14-15 where the diagrams appear at the bottom of the page. But, I agree that usually it is not easy to place images where you want in LaTeX.
- DeusCodex 3y agoThis is such a amazing little book. I love it, AI is hard for me to understand but this book makes it very easy to grasp some of the concepts. Thanks for sharing
- kristopolous 3y agoUsually I'm a harsh critic of text like this because casual language and what look like casual words but are actually strictly defined domain specific technical definitions are utterly indistinguishable. However! This book back-references its appendix with grey underlines thus signaling that something has a technical definition and is jargon. For instance, "loss" is really common English. In ML it's a loss function. You can clearly see it's a special word in this world in the text. Other examples include weights, capacity and channel. I don't have to sit there confused trying to guess which English words are being used in special ways. This discipline is fantastic. In some texts, such terms might be italicized but that behavior has seem to fallen out of practice. As someone who isn't a professional mathematician, hints like these help greatly.
- rwoerz 3y agoI fully agree with your general critique. It is a common bad habit in science to use common words with an uncommon meaning without any explanation. I remember me sitting in a lecture about cryptology and wondering how that "I can prove to know a SECRET without revealing it" is supposed to work. I just did not realize that SECRET just meant "random-looking string" instead of something like "I know where the money is hidden".
- chaxor 3y agoIf it's a map to the hidden treasure (as in the exact bits of the image of the map) then it's kind of the same thing right? But yes, the non-uniqueness of expressing similar ideas can make things difficult there.
- tpoacher 3y agoYou say this about exactness, but my experience with much of science and ML in particular is the opposite. People still haven't decided what the difference between AI and ML is, for instance, but somehow still insist to treat the two as obviously separate in conversations. My experience has been that the naming problem is alive and well in the sciences; and it'sfar more problematic than in programming and variable naming.
- abricq 3y agoI had a course named `Deep Learning` by François Fleure at EPFL, and he is a really an amazing professor, able to share his passion alongside explaining very advanced topics. It does not surprise me to see that his books are of very high quality ! The course was focusing on all of the mathematical aspects of Deep Learning, starting from the simple understanding of the gradient descent algorithm to (trying to) understand how transformers work. There was also quite a lot of computer science involved and lots of practical assignments. One of the 2 projects of this course was to design from scratch in Python or C++ a DNN framework (roughly an API like pytorch or tensorflow) which required to really think properly about which architecture to use for your code. The minimum requirements only asked to implements a few activation, normal layers and convolutional layers but you go beyond that and implements all kind of layers. Lots of fun. This course remains as one of my favorite courses.
- stevesimmons 3y agoHis website also has a version for printing out on 36 sheets of paper and folding into a real book: https://fleuret.org/public/lbdl-a5-booklet.pdf https://fleuret.org/public/lbdl-a5-booklet.pdf
- sidcool 3y agoFor my level of knowledge, this is a bit advanced book. Anything more basic?
- Version467 3y agoYou haven't specified in which way this is too advanced for you. Still, I'll take a stab at recommending some other resources. 1: Practical Deep Learning by fast.ai - a (free) hands on course that's designed to get you to making something useful as quickly as possible. 2: Neural Networks Zero to Hero from Andrej Karpathy - A Series of Youtube Lectures that requires only basic python knowledge and takes you all the way up to a simplified implementation of the tech inside gpt models. 3: Neural Networks from Scratch by Sentdex. A book that's explicitly written to teach you the basics. Doesn't cover stuff like Transformers and other advanced concepts, but really takes its time with the basics. Take a look at all three of them. They all have a different teaching style and I'd guess that at least one of them will gel with you.
- sidcool 3y agoThis helps. Thanks.
- przem8k 3y agoGreat writing! I love how this book gets to the point right from the start, answering one of my questions about deep learning (how did this start?) in the very first sentence: "The current period of progress in artificial intelligence was triggered when Krizhevsky et al.[2012] showed that an artificial neural network (..) could beat complex state-of-the-art image recognition methods by a huge margin (..)"
- sreeramvenkat 3y agoAny recommendations for a set of hands on exercises that go well with this book ?
- _giorgio 3y agoProbably his course, all in pytorch. https://fleuret.org/dlc/ https://fleuret.org/dlc/