Books and/or Readings for AI and SP

CompMathQuant · Post by **CompMathQuant** » Tue Jul 17, 2012 12:30 pm

Greetings to all

Could someone please recommend book/s and/or readings for Artificial Intelligence and Signal Processing.

Thank you very much.

A

HankScorpio · Post by **HankScorpio** » Tue Jul 17, 2012 12:54 pm

For signal processing take a look at the books by Steven Kay (statistical signal processing).

CompMathQuant · Post by **CompMathQuant** » Tue Jul 17, 2012 6:43 pm

HankScorpio,

Thank you very much for taking the trouble.

I'll definitely have a look at the book and once again sincere thanks.

A

frstwrldprblm · Post by **frstwrldprblm** » Tue Jul 17, 2012 8:36 pm

AI a modern approach

is heavily referenced as "the" AI book to start with.

MrMagoo · Post by **MrMagoo** » Wed Jul 18, 2012 3:31 am

Follow my links below :

If you want to learn from scratch and put serious study time, you can understand the basic framework, then slowly jump to the state of art.

hardly u can get a better beginner's online stuff.

I took these 2 for fun last year. I liked, even though i knew the subject at a higher level than presented.

beginner's AI class (co-taught by P.Novig, co-author of "the AI" book.)

Machine Learning basics

I barely have time now, but i would seriously consider any coursera courses :

this one may interest you.

digital signal processing

CompMathQuant · Post by **CompMathQuant** » Thu Jul 19, 2012 7:14 am

frstwrldprblm- Thank you very much for the recommendation.

I have got the book, just now. From the look of first few chapters, it does really look right kind of book for me.

Thank you once again for your very kind help.

A

CompMathQuant · Post by **CompMathQuant** » Thu Jul 19, 2012 7:30 am

MrMagoo- Thank you very much for the suggestion.

Before posting the message here, I, indeed, was looking at Coursera courses. I am having a look at the course available over there once again.

I also have found AI online course notes from P.Novig. I will, for sure, be studying the notes and watching the videos which are available on the portal. The notes and video seems me to be very interesting and contents are what I was looking for.

Thank you once again for taking time in replying the message.

A

bluelou · Post by **bluelou** » Thu Jul 19, 2012 5:16 pm

I can't speak to AI more broadly but I just finished the Coursera ML course and I plan to take the Probabilistic Graphical Models (PGM) course in Sep. The ML course is taught very well. It's very strong on the intuition behind various ML techniques but it's a bit light on the math/technical aspects underlying the subject. I hear the PGM course is more in-depth and very time consuming.

For an ML book where you can follow along from the code figures (plus Python code at website) you may want to look at Machine Learning by Stephen Marsland. For, AI, I would guess that you want to cover particle filters. This book mentions them but only covers Kalman filters in detail.

gax · Post by **gax** » Thu Jul 19, 2012 6:42 pm

Take a look at: Pattern Theory: The Stochastic Analysis of Real-World Signals by David Mumford and Agnès Desolneux. It's a beautiful book.

jslade · Post by **jslade** » Thu Jul 19, 2012 9:26 pm

One of the problems with all the AI or machine learning books I've looked at (including my 2nd edition of Norvig, which I would not recommend to anyone but my enemies): they're more interested in classification problems than time series problems. Most ML books have a pretty cursory treatment of TS, generally when addressing Hidden Markov or reinforcement learning type things.

There is also the matter of noise in general, let alone time dependent noise, which seems an afterthought to most AI/ML guys, unless they're covering Kalmany things.

I guess if you know what you're doing and are well grounded in signal processing techniques, it doesn't matter so much, but it can be confusing, and you can get into all kinds of trouble.

Maybe that Mumford book is better at covering such issues; it certainly looks really good.