Machine Learning at U of C
This page contains a list of topics, definitions, and results from Machine Learning course at University of Chicago.
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Week 1
Learning problem
Given a distribution on . We want to learn the objective function (with respect to the distribution ).
Learning Algorithms
Let Z be the set of possible samples. The learning algorithm is a function that maps a number of samples to a measurable function (denoted here by F a class of all measurable functions). Sometimes we consider a class of computable functions instead.
Loss function
Suppose the learning algorithm outputs h. The learning error can be measured by
One can prove that minimizing this quantity could be reduced to the problem of minimizing the following quantity.
And that's the reason why we try to learn