Abstract
Artificial Iintelligence and machine learning are concerned with
automation of intelligent behavior.
Main techniques in Artificial Intelligence can be divided into the
following groups: "Searching" , "Planing" , "Optimization Techniques”
, "Reasoning" and "Approximation Methods". Artificial intelligence is
also used in applications, such as search engines, expert systems, the
analysis and forecast of stock prices and handwriting or speech
recognition.
Although many tedious tasks can be automated by modelling the behavior
of a (computer) system manually, many problems require that a system
can adapt its reponses based on feedback on former actions, i.e.,
learn how to act in a better way in the future. Other tasks are just
too large-scale for humans to overview, so help from computers is
needed.
Machine Learning (also known as Data Mining, Pattern Recognition, Data
Analysis, and Classification) is a research area at the intersection
of computer science, artificial intelligence, mathematics and
statistics, that addresses these problems. It covers general methods
and techniques that then can be applied to a vast set of applications
such as predicting customer behavior, steering a robot, detect spam,
and predict the folding of a protein, to name just a few.
In this course we provide different practical topics from the area of
data mining and machine learning, the task is to design and implement
an application. This application should be applied on data from
different domains (provided by us).
The project allows students to gain practical knowledge and
capabilities in the usage of data mining and machine learning
algorithms.
- Each topic is intended for a small group of 3-4 students.
- Software should be written in Java or C++.
- Each topic consists of a tool and its proof-of-concept application in an example domain.
- Groups can start immediately.
- Each group is supposed to give at least two presentations:
- a first presentation about ongoing work, showing a first implementation and commenting on problems (around mid term),
- a final presentation of the whole work (end of term).
- You can register for topics from now on via email.
- For topics please contact Rasoul Karimi
Instructor: Rasoul Karimi
