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From Lance Norskog <goks...@gmail.com>
Subject Re: Recommended reading
Date Wed, 09 Mar 2011 03:43:34 GMT
At the Hacker Dojo they taught a Machine Learning class based on the
Stanford CS229 materials. Most of the tutorials were dense but very
well-written.

But the class was quite advanced for most of the programmer
participants. It was 30 years since I had watched someone write Greek
letters in front of a class. A struggle to be sure, but the instructor
loved doing it.

They are now doing two classes, beginning and advanced. The Stanford
CS229 is the advanced. The beginning class uses a stats & other things
course from San Jose State.

The Stanford professor/grad student crew won an autonomous vehicle
competition 2 years in a row. They have this great video of the car
doing a stunt: accelerate in reverse, slam the wheel and brakes, and
do a skidding U-turn backwards into a parking space. They recorded a
stunt driver and set up the car to switch between closed- and
open-loop controls.

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
>>
>



-- 
Lance Norskog
goksron@gmail.com

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