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Ask HN: Best books on AI?

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Re: Ask HN: Best books on AI?

#71

Post by cs702 »

j_s wrote: post #69

First, read fucking Hastie, Tibshirani, and whoever. Chapters 1-4 and 7. If you don't understand it, keep reading it until you do. You can read the rest of the book if you want. You probably should, but I'll assume you know all of it. Take Andrew Ng's Coursera. Do all the exercises in Matlab and python and R. Make sure you get the same answers with all of them. Now forget all of that and read the deep learning book.…

I would add one more item to the list: replicate the results of at least a few "classic" deep learning papers from scratch in one of the popular frameworks (TensorFlow, Torch, Caffe, etc.), instead of downloading code written by others. For example, build and train Alexnet or one of the VGGnets, a Word2Vec model, an image captioning model (joint CNN and LSTM RNN), and a pong- or breakout-playing AI (CNN with reinforcement learning). It's possible to do all of this on a single machine with a relatively inexpensive GPU.

Re: Ask HN: Best books on AI?

#72

Post by adastra »

shoshin23 wrote: post #8

Superintelligence by nick bostrom. It's a book that explores how superintelligence could emerge, the different ways it can take off and what it means to us as humans. More importantly, the book takes on the difficult task of figuring out ways to make sure the AI is safe and not land up in the wrong hands. Pretty interesting read that doesnt really require technical know-how.

The book is interesting, but the level of detail he goes into in some of his speculation is completely unjustified. It's kind of ridiculous.

"There's no sense in being precise when you don't even know what you're talking about." - von Neumann

Re: Ask HN: Best books on AI?

#73

Post by _xhok »

Get your feet wet:

* http://cs231n.stanford.edu/ (the course notes are excellent)

* http://neuralnetworksanddeeplearning.com/

* http://www.deeplearningbook.org/

Use Tensorflow to train a few small neural nets. Move on to CNNs and RNNs. Make sure you actually do this. By this point you'll have read a lot, and retain none of it if you don't put it to use. Look at reinforcement learning. Use the book by Sutton and Barto, the new edition: https://webdocs.cs.ualberta.ca/~sutton/book/the-book-2nd.htm... Read the first 4-5 chapters, then go online and read about Deep Q learning, policy gradients, DDPG, etc. Then try to solve some problems on OpenAI Gym.

Once you have an idea of the kinds of problems you can solve, and have a couple you're interested in, go back and learn the foundational math, and start reading research papers.

In general, start with modern books that mention deep learning. With older books or high-level-overview books, you'll get frustrated when you see something cool on /r/machinelearning and can't find any mention of it in the book.

Re: Ask HN: Best books on AI?

#74

Post by metaobject »

abecedarius wrote: post #62
nextos wrote: post #35

Earlier quoted context omitted.

I love Paradigms of Artificial Intelligence by Peter Norvig much more than AIMA, which I found excessively encyclopedic and shallow. While some will argue it is dated, I think it presents many timeless ideas that will get in vogue soon with little tweaks to their inference schemes. Same for The Art of Prolog.

PAIP is one of my favorite books ever, but taken as a book about the craft of programming, not about AI. AI has grown, and the broadness of AIMA matches the subject. (It does need another update, and I heard they're working on one.)

PAIP is also very, very high on my list as well. I'm very pro-lisp and still develop new projects in lisp (CL, Scheme) and promote it when/where I can. But the person who picks up PAIP wanting to learn AI might not necessarily want to worry about picking up lisp programming skills at the same time (nor is learning lisp strictly necessary). This is why AIMA is still the best option, IMO, because it employs a language agnostic approach.

Re: Ask HN: Best books on AI?

#75

Post by metaobject »

stesch wrote: post #59
nextos wrote: post #35

Earlier quoted context omitted.

I love Paradigms of Artificial Intelligence by Peter Norvig much more than AIMA, which I found excessively encyclopedic and shallow. While some will argue it is dated, I think it presents many timeless ideas that will get in vogue soon with little tweaks to their inference schemes. Same for The Art of Prolog.

I had the feeling it was more of a Common Lisp book than AI book.

It's both, but the AI coversge is quite out of date.

Re: Ask HN: Best books on AI?

#77

Post by cscurmudgeon »

nextos wrote: post #35
arihant wrote: post #26

You cannot really go practical in AI without academic rigor. You can do recipes of what's already been done using a TensorFlow book, but that's how far one can go. If one is serious in getting in AI today, a great way to do is read the following books, in order: 1. AI: A Modern Approach by Stuart Russell and Peter Norvig. 2. Deep Learning by Ian Goodfellow and Yoshua Bengio. It is amazing how approachable both books…

I love Paradigms of Artificial Intelligence by Peter Norvig much more than AIMA, which I found excessively encyclopedic and shallow. While some will argue it is dated, I think it presents many timeless ideas that will get in vogue soon with little tweaks to their inference schemes. Same for The Art of Prolog.

PAIP is awesome. Will make you a better thinker and developers. A truly hidden gem.

Re: Ask HN: Best books on AI?

#80

Post by kleiba »

Scarblac wrote: post #43
kleiba wrote: post #22

Earlier quoted context omitted.

Not surprisingly, I would say, since I wouldn't count speech recognition as an AI task.

Nothing is counted as an AI task after someone finally manages to do it.

I anticipated that argument, but I wouldn't have considered ASR an AI task even before it was first attempted.
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