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From Krishna Sankar <ksanka...@gmail.com>
Subject Re: Recommended reading
Date Wed, 09 Mar 2011 05:44:08 GMT
For Matrix computations, I like Watkins[1] better.
Cheers
<k/>
[1] 
http://www.amazon.com/Fundamentals-Matrix-Computations-Applied-Mathematics/
dp/0470528338/

On 3/8/11 Tue Mar 8, 11, "Vipul Pandey" <vipandey@gmail.com> wrote:

>> I also recommend the iTunesU course and the notes to this class.  I
>> actually printed out a copy of the lecture notes and had them spiral
>> bound.
>I'm not surprised. I took that class and I believe Andrew Ng does a *very
>good job teaching the course.
>But going through the videos and the lecture notes should be sufficient to
>learn a great deal on one's own.
>
>I also watched Strang's lecture  sometime back (again on iTunesU) and they
>are pretty good too - haven't read his book though.
>
>Also, while we are at it : any suggestions on a book on matrix
>computations/decomposition/factorization etc.?
>
>How's this one?
>http://www.amazon.com/gp/product/0801854148/ref=s9_simh_gw_p14_d0_i1?pf_rd
>_m=ATVPDKIKX0DER&pf_rd_s=center-3&pf_rd_r=0ESQ3KDY8MJ1AWWG8PFR&pf_rd_t=101
>&pf_rd_p=470938811&pf_rd_i=507846
>any idea? any other suggestion?
>
>Thanks
>~Vipul
>
>On Tue, Mar 8, 2011 at 4:38 PM, Ted Dunning <ted.dunning@gmail.com> wrote:
>
>> They won't.  Strang is the answer for the linear algebra part.
>>
>> On Tue, Mar 8, 2011 at 4:18 PM, Mike Nute <mike.nute@gmail.com> wrote:
>>
>> > I also recommend the iTunesU course and the notes to this class.  I
>> > actually printed out a copy of the lecture notes and had them spiral
>> > bound.  The Hastie/Tibshirani/Freidman book is also excellent.  Not
>> > sure if those will help as much with the linear algebra though (except
>> > the appendix).
>> >
>> > On Tue, Mar 8, 2011 at 12:35 PM, Vipul Pandey <vipandey@gmail.com>
>> wrote:
>> > > For Machine Learning - i would recommend looking at
>>cs229.stanford.edu
>> .
>> > It's a very nicely taught course with super helpful lecture notes -
>>and
>> you
>> > can get all the videos in youtube or iTunesU.
>> > > http://itunes.apple.com/itunes-u/machine-learning/id384233048
>> > >
>> > > The section notes for this course will give you enough review
>>material
>> on
>> > linear algebra and probability theory to get you going.
>> > >
>> > > ~Vipul
>> > >
>> > >
>> > > On Mar 8, 2011, at 8:42 AM, jeremy@lewi.us wrote:
>> > >
>> > >> Quoting Vasil Vasilev <vavasilev@gmail.com>:
>> > >>
>> > >>> Hi all,
>> > >>>
>> > >>> Can someone recommend me good books on Statistics and also on
>>Linear
>> > Algebra
>> > >>> and Analytic Geometry which will provide enough background for
>> > understanding
>> > >>> machine learning algorithms?
>> > >>>
>> > >>> Regards, Vasil
>> > >>>
>> > >>
>> > >> The goto book for linear algebra is "Introduction to Linear
>>Algebra"
>> by
>> > Gilbert Strang. His lectures are also available online at.
>> > >>
>> > >>
>> > 
>>http://ocw.mit.edu/courses/mathematics/18-06-linear-algebra-spring-2010/
>> > >>
>> > >> You could probably also find a machine learning class lecture
>>online
>> at
>> > MIT.
>> > >>
>> > >> J
>> > >>
>> > >
>> > >
>> >
>> >
>> >
>> > --
>> > Michael Nute
>> > Mike.Nute@gmail.com
>> >
>>



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