13 ms·
Free “Deep Learning” Textbook by Goodfellow and Bengio Now Finished
- rtnyftxx 11y agourl is http://www.deeplearningbook.org/ http://www.deeplearningbook.org/
- newman314 11y agoPDF version is: http://www.deeplearningbook.org/front_matter.pdf http://www.deeplearningbook.org/front_matter.pdf
- kolencherry 11y agoUnfortunately, that's just the ToC and the bibliography. It looks like their "contract with MIT Press forbids distribution of too easily copied electronic formats of the book."
- wyldfire 11y agoDoes that mean there's a fifteen-step asciidoc/gitbook/LaTeX build that is freely distributed? Because I'm willing to spend a few minutes building a pdf for the sake of getting good content.
- coolsunglasses 11y agoDoubt it. We talked to MIT Press about publishing our book and they were extremely hostile to having any way for our readers to produce an un-DRM'd PDF, which is how our book is currently distributed. Actually, they were mostly just very hostile and unpleasant. This is among the many reasons why we're probably staying independent and printing the book ourselves - so that the digital version stays unencumbered among other things.
- cuckcuckspruce 11y agoUgh, MIT Press, the same organization that won't allow easy distribution of things like the Wizard Book.
- teraflop 11y agoIt's pretty easy to just run "Save as PDF" on each chapter individually, and then stitch them together with: pdftk $(ls -tr *.pdf) cat output DeepLearningBook.pdf Out of respect for the authors' contract, I won't post the resulting file here, but anyone can reproduce it with about 5 minutes of work.
- gherkin0 11y agoUnfortunately, according to the site, the HTML pages themselves have problems, such as missing parens and incorrect math symbols.
- mcguire 11y agoThat would give you a PDF version of the web page, right? Wouldn't you still have problems with "some things like subscript expressions do not render correctly"?
- throwaway287391 11y agoIn case anyone else has trouble with the "Save as PDF" part, I did it successfully using Firefox on OSX: from the print menu, choose "show details" and change all headers/footers to "--blank--" so there's no ugly URLs/dates in the corners, then press PDF -> "Save as PDF". (In Chrome, on the other hand, saving/printing as PDF chopped each page into quarters for me...) At least in the one chapter I've saved so far, all the math notation renders just like in the HTML version.
- deleted 11y ago[deleted]
- wololobot 11y agohttps://mega.nz/#!vZVjlazb!rWcCCC7iv1RI9ssjdUFj7iTpphUCIFQY3WCuj79gJwU https://mega.nz/#!vZVjlazb!rWcCCC7iv1RI9ssjdUFj7iTpphUCIFQY3... Preview: http://i.imgur.com/5OXv28R.png http://i.imgur.com/5OXv28R.png Call me evil but I did it:p
- dandermotj 11y agoSomebody please package the html into a pdf!
- bootload 11y ago"Can I get a PDF of this book? No, our contract with MIT Press forbids distribution of too easily copied electronic formats of the book."
- whatok 11y agoI was able to print to PDF in Chrome and combined the PDFs in Acrobat.
- TheCabin 11y agoI guess this could be automated. For instance, you could download all html files using a plugin like "Download Them All" with a renaming mask like "inum-nameinum.ext" and then try: find . -iname '*.html' -exec wkhtmltopdf {} {}.pdf \; There are also tools to convert the resulting files to a single pdf. The only problem I got is, that the woff fonts are not rendered by "wkhtmltopdf" :-/ Ideas?
- cced 11y agoThis type of thing is what gets people thinking about a way around the no-pdf solution.
- MasterScrat 11y agoThis looks interesting, can't wait to dig into it. Another great great free online book on this topic: http://neuralnetworksanddeeplearning.com/ http://neuralnetworksanddeeplearning.com/
- dasboth 11y ago+1 for that recommendation, a really good resource.
- taneq 11y agoI'm working my way through that at the moment and so far it's pitched rather well (at least for my prior experience), describing things simply and concisely but still with enough background that it's easy enough to see where everything fits.
- chatman 11y agoIf there are restrictions around distribution formats, it is misleading to call it "free".
- gcr 11y agoIf only we could convince publishers to publish GFDL or Creative Commons licenses the way we've convinced some software companies to commercialize open source software...
- sherjilozair 11y agoThe FSF does not have a monopoly over the word "free". For a lot of people, "free" means as in "free beer", which this book is, in the online format.
- MistahKoala 11y agoA bit unrelated, but can anybody tell me what typeface is used for the body text in the PDF?
- heinrichf 11y agoThe default TeX font: https://en.wikipedia.org/wiki/Computer_Modern https://en.wikipedia.org/wiki/Computer_Modern
- amelius 11y agoHere's a handy service for that: https://www.myfonts.com/WhatTheFont/ https://www.myfonts.com/WhatTheFont/ Just submit a screenshot image of some glyphs of the font at a reasonable size, and let the service figure out the font!
- nani1002 11y agoPretty handy service. Any idea what's the mechanism behind the recognition software?
- gcr 11y agoThe font is "Computer Modern," the default LaTeX font. Nothing screams "I'm an academic engineering textbook!" quite like Computer Modern.
- osoba 11y agoDoes anybody know how to make the book actually readable? http://i.imgur.com/C4rhclk.png http://i.imgur.com/C4rhclk.png
- therobot24 11y agoWhen i turned off scripts via NoScript it turned to readable again
- osoba 11y agoThe text looks readable but the formulas are missing pieces since the TeX fonts arent loaded. Printing to PDF worked for me
- gcr 11y agoYou can print to a pdf on Chrome. That comes out nicely for me.
- osoba 11y agoThat worked. Thanks
- davnicwil 11y agoThanks! Related to printing - this made me chuckle: > Printing seems to work best printing directly from the browser, using Chrome. Other browsers do not work as well. In particular, the Edge browser displays the "does not equal" sign as the "equals" sign in some cases. Of all the printing bugs for a maths/logic heavy text! Can just visualise the head banging against the desk upon discovering this one, having struggled with understanding something for hours - well ok, either the universe is broken or... oohhhhhhh :-D
- jawilson2 11y agoLooks fine here: http://imgur.com/0pQ3a53.png http://imgur.com/0pQ3a53.png
- deleted 11y ago[deleted]
- phatbyte 11y agoThanks for this. I'm currently re-learning statics/probabilities and linear algebra so your book will be useful in a few months down the line ;)
- knoble 11y agoWould you mind sharing any of the resources you are using for re-learning? I've been meaning to do the same.
- gamapuna 11y agoA couple of friends recommended these:- (Not sure if they are relevant though for deep learning specifically) 1) http://ocw.mit.edu/courses/mathematics/18-06-linear-algebra-spring-2010/ http://ocw.mit.edu/courses/mathematics/18-06-linear-algebra-... 2) https://www.khanacademy.org/math/linear-algebra/vectors_and_spaces https://www.khanacademy.org/math/linear-algebra/vectors_and_... If anyone knows anything else (relevant to deep learning) could you please share :)
- exox 11y agoIntroduction To Statistical Learning: http://www-bcf.usc.edu/~gareth/ISL/ http://www-bcf.usc.edu/~gareth/ISL/ Is an excellent statistical learning reference.
- lindbergh 11y agoJust saying, but if you want to hop onto the ML bandwagon (for instance), then don't bother going over linear algebra or probabilities first, and instead just learn what you need as you go. For example, the first sections of this book are already devoted to getting you on the right track, and it's somewhat standard to do so. And besides, there's no need in learning what are rotation matrices if you won't use them.
- yompers888 11y agoAs a counterpoint, if parent is interested in taking ML further, a solid foundation in linear algebra will be huge when more advanced signal processing applications come up.
- max_ 11y agoThey better release a PDF in the future.
- patmcguire 11y agoDon't quite get the complaints about it not being available in PDF. "We'll publish your book, and you can give it away for free as long as you make people click through to each chapter" is a much, much better deal than I would expect from a big publisher.
- stygiansonic 11y agoGive an inch, take a mile.
- baltcode 11y agoPretty much ... the only edge case I feel for is having an offline copy in places with low or expensive internet access. Like parts of the developing world. Clicking through isn't such a big deal.
- patmcguire 11y agoIn the old days IE had a feature for saving pages for offline reading that would ask you how deep to recursively traverse. It was considered hilarious to set it for 99 on the school dialup connection.
- jjawssd 11y agoRemove Facebook link
- baltcode 11y agoFirst impressions: 1. It also covers "classical" artificial neural networks, i.e., things like backprop from before Hinton and others made breakthroughs for deep learning. This means you can start with this book even if you are new to ANNs. The later sections cover "real deep learning". 2. The language is great for beginners and users. You don't have to be an advanced math geek to follow everything. They seem to cover a fair amount of ground too, so its not dumbed down either. 3. I guess it covers most of the underlying theory and practical technicques but is implementation neutral. You should probably pick up a tutorial for your favorite implementation like Theano, TensorFlow, etc. All in all, I like it a lot.
- ogrisel 11y agoThe old backprop from the 80's / 90's is still in use and the primary way to train deep nets. We tend to call it SGD (on a composition of differentiable functions) nowadays but it's the same algorithm.
- deleted 11y ago[deleted]
- wodenokoto 11y agoThe HTML format is quite peculiar. It kinda looks like someone ran the original PDF through PDF.js and saved the rendered output to a HTML file.
- rememberlenny 11y ago"This format is a sort of weak DRM required by our contract with MIT Press. It's intended to discourage unauthorized copying/editing of the book. Unfortunately, the conversion from PDF to HTML is not perfect, and some things like subscript expressions do not render correctly. If you have a suggestion for a better way of making the book available to a wide audience while preventing unauthorized copies, please let us know."
- yorwba 11y agoThe HTML source contains this: <!-- Created by pdf2htmlEX (https://github.com/coolwanglu/pdf2htmlex https://github.com/coolwanglu/pdf2htmlex) -->
- Edmond 11y agothey just need to use the --zoom option in pdf2htmlEX when generating the html. 1.5 zoom should be good.
- kkylin 11y agoCan any practitioners / experts out there comment on the range of topics? For example, I understand the book to be introductory, and so the scope is likely somewhat limited. But how close does it get you to the ANNs currently in use, at least conceptually if not in complete detail? Thanks!
- ericjang 11y agoNon-expert DL practitioner here. The coverage is very good - if I were running some kind of "Deep Learning onboarding class" for a university or tech company, this is what I would present. My favorite aspect of this book is that it provides a graphical models interpretation of DL methods, which is the most powerful perspective we have right now to reason about model design (instead of some large black box function that we train end-to-end without knowing what's in between). It also explains some fairly recent models and techniques well (VAE, DCGAN, regularization) that form the basis of more complex architectures. If you understand the models here, you should be able to understand the design choices made in more complex architectures. Thanks to Goodfellow, Bengio, and Courville for this excellent work.
- kkylin 11y agoGreat, that's very helpful to know. Thanks!
- 1024core 11y agoDoes it cover new(er) topics like Deep Reinforcement Learning, Residual Networks, Inception nets, etc.?
- kleiba 11y agoHave you tried looking at the TOC and index?
- uptownfunk 11y agoThis looks great, any other recommendations for enjoyable reads on ml/stat learning? ESL ISLR doing Bayesian data analysis w/ jags/Stan bda3 - gelman prob graphical models Convex analysis - Boyd adv data analysis from elem pov - shalizi Trying to build out my library. I have a background in prob/stats/analysis and measure theory/linear algebra and also knowledge of algorithms and data structures at the advanced undergrad level, So I'm not too concerned about technical depth just want to enjoy a good technical expository and gain intuition.
- maxaf 11y agoAthena (http://athenapdf.com/ http://athenapdf.com/) does a phenomenal job at turning those HTML pages into convenient PDF files.
- rajeevk 11y agospent lot of time to convert each pages using this website and merged the pdfs into single pdf and then found that Athena has not done the conversion correctly. The diagrams not converted correctly. Waste of time!!
- j2kun 11y agoI spent a few weeks closely reading this book and I have to disagree with the majority here. I didn't like the book at all. And I am an advanced math geek. My main issue is that the book tells you all about the different parameter tweaks, but passes little concrete wisdom to the reader. It doesn't distinguish between modeling assumptions, and it replaces very simple explanations of concepts with complicated paragraphs that I can't make sense of. I think it boils down to something that I have been feeling and hearing a lot in the past few years: the statistical jargon is so overwhelming that the authors can't explain things clearly. I can point to many examples in this book that I feel are unnecessary stumbling blocks, but the fact is that I'll spend an hour or two discussing parts of this book with a room full of smart machine learning researchers, and at the end we'll all agree we don't understand the material better than we did at the start. On the other hand, I'll read research papers that don't force the statistical perspective down the reader's throat (e.g. http://arxiv.org/abs/1602.04485v1 http://arxiv.org/abs/1602.04485v1) and find them very easy to understand by comparison. It might be a cultural difference, but I've heard this complaint enough from experts who straddle both sides of the computational/statistical machine learning divide that I don't think it's just me.
- gherkin0 11y agoDo you know of any books that don't have the problems you speak of?
- p1esk 11y agoThat's disappointing. I was really looking forward to reading the book.
- kleiba 11y agoYou still should, I think. I mean, at least give it a try. Different people can have completely different experiences when reading the same material. Perhaps you will love it, perhaps you will agree with the OP. In any event, it's worth getting it straight from the horse's mouth.
- 11y ago
- j2kun 11y agoI spent a few weeks closely reading this book and I have to disagree with the majority here. I didn't like the book at all. And I am an advanced math geek. My main issue is that the book tells you all about the different parameter tweaks, but passes little concrete wisdom to the reader. I think it boils down to something that I have been feeling and hearing a lot in the past few years: the statistical jargon is so overwhelming that the authors can't explain things clearly. I can point to many examples in this book that I feel are unnecessary stumbling blocks.
- liviu- 11y agoFor anyone interested, Goodfellow is answering questions about the book at: https://www.reddit.com/r/MachineLearning/comments/4domnk/the_deep_learning_textbook_is_now_complete/ https://www.reddit.com/r/MachineLearning/comments/4domnk/the...
- muyuu 11y agoI don't claim to have a solution, but these models of book monetisation really seem doomed. What are the chances that I will buy this book just because they made it artificially harder for me to download it? Probably a net negative.
- deleted 11y ago[deleted]
- arbre 11y agoDoes this book mention attention models?