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\lecture{CS5350: Machine Learning}{HW0: Basic machine learning concepts}{Due 28 Aug 2008}

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\section{Student Survey}
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Please note the following information on your assignment:

\bee
\i Which of the following courses have you taken:
 Differential calculus; Integral calculus; Multivariate calculus;
 Linear algebra; Probability and statistics; Artificial Intelligence;
 Algorithms; Computer vision; Natural language processing; Robotics;
 Optimization (linear, quadratic, convex, etc.)

\i List a few (research) topics that interest you.

\i How would you rate your programming skills (1-10, 10 best)?  How
would you rate your math skills?
\ene

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\section{Written Exercises}
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Answer the following questions in 25-100 words each:

\bee 

\i What is the difference between supervised, unsupervised and
reinforcement learning?

\i List at least two real-world problems (other than those discussed
in class) for each of the categories: supervised, unsupervised and
reinforcement.  For one of the supervised problems, what is the form
of the output and what might be a reasonable input?  For the
reinforcement learning problem, what might be the state space, action
space and reward function?

\i What is inductive bias?

\i What is generalization?
\ene

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\section{Matlab Exercises}
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Read the Matlab tutorial at
%\url{http://www.mines.utah.edu/gg_computer_seminar/matlab/matlab.html}.
\url{http://www.math.utah.edu/faq/matlab/tutorial/} What are each of
the following operations doing?  What is their result?  (If an
operation fails, tell me why.)

\bee
\i \tt{>> [1 2 3 ; 4 5 6 ; 7 8 9] * [10 ; 11 ; 12]}
\i \tt{>> [eye(3) ; 0 1 2]}
\i \tt{>> x = rand(4);} \\
   \tt{>> repmat(x,2,2) - [x x ; x x]}\\
\i \tt{>> [0 1 2 ; 2 1 0 ; 1 2 0] * [0 1 1]}
\i \tt{>> [0 1 2 ; 2 1 0 ; 1 2 0] * [0 1 1]'}
\i \tt{>> x = [];} \\
   \tt{>> for i=1:10, x = [x i]; end;} \\
   \tt{>> x}
\i \tt{>> inv(eye(5))}
\i \tt{>> x = rand(10000);} \\
   \tt{>> sum(sum(x>0.5)) / 10000}
\i \tt{>> x = rand(20);} \\
   \tt{>> x([1 5 20], 5:10);
\ene

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