Teaching Machine Learning: Student Project Reports for CPSC 599.66 and 601.66 Winter 2007
Date
2007-04-25
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Abstract
Teaching machine learning has two parts. One part is the lectures.
These can be found under www.cpsc.ucalgary.ca/~mrichtet/ml. But lecturing is
only half of the story. That is, because passive learning by listening does
not provide the same expertise compared to active learning by doing. For this
purpose a project work was required. Students had the choice to work on their
own or to form a group of two. At the beginning of the course, after some
introduction and overview, the projects started. The start had the following
steps: 1) Selecting a domain of application as, e.g. spam filters, playing
games, cooperative multiagents etc. 2) Formulating a learning goal in that
domain, as improving cooperation. The choice was completely free. 3) Selecting
one or more candidates for learning techniques presented in the course that
were focused in the sequel. These topics were presented first very early and
then in some more detail at midterm. In this volume the final reports are
listed. Particular emphasis was put on the aspects of the difficulties that
occurred during the project and how to overcome them. The difficulties had
different sources. The major ones are problems with the tools and getting
enough data, or underestimating the complexity. The free choice of the
application domain had the consequence that the authors were quite familiar
with it, could use existing environments and use the results for further
activities like masters or PhD theses. Formal projects implementation details
are available, write to mrichter@cpsc.ucalgary.ca
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Computer Science