Data Warehousing and Machine Learning (Data Mining)


Spring 2002

What is Data Mining ?

Together, data warehousing and machine learning comprise what is known as data mining or knowledge discovery in databases (KDD). Data warehousing can be briefly described as creating a copy of transaction data specifically structured for query and analysis. Machine learning is concerned with computer programs that automatically improve their performance through experience.

A more detailed description of data mining and the contents of this course can be found in a PDF document (also available as a PostScript document).

Instructors

Michael O. Akinde, room no. E1-201b.
Uffe B. Kjśrulff, room no. E1-101a.

Data Warehousing Text

Machine Learning Textbook

Tom Mitchell (1997), Machine Learning, McGraw Hill.

Available at Aalborg Centerboghandel, Fredrik Bajers Vej 7B, at a price of DKK 470 (10% discount for students).

Errata for printings one and two available in PostScript and PDF formats.

Review of the book available in PostScript and PDF formats.

Lecture plan (and slides)

Topic

Date & time

Room

Introduction to Data Warehousing Mon 25 Feb 10:15 E1-214

Introduction to Machine Learning Wed 27 Feb 10:15 E1-214

Advanced Multi-dimensional Modelling Thu 21 Mar 12:00-16:00 E1-212

Decision Trees Wed 6 Mar 10:15 E1-214

Building the Data Warehouse Thu 21 Mar 12:00-16:00 E1-212

Artificial Neural Networks Wed 13 Mar 10:15 E1-214

Complex OLAP Fri 22 Mar 8:00-16:00 E1-214

Bayesian Learning: MAP & ML Wed 3 Apr 8:30 E1-214

Data Mining - A Database Perspective Fri 5 Apr 9:30-16:00 E1-212

10 

Bayesian Networks, EM Algorithm Wed 3 Apr 10:15 E1-214

11 

Some Other Machine Learning Algorithms Wed 10 Apr 10:15 E1-214

12 

DW Workshop Fri 17 May 8:30 E1-214

13 

DW Workshop Fri 17 May 10:15 E1-214

14 

ML Workshop Fri 17 May 12:30 E1-214

15 

ML Workshop Fri 17 May 14:15 E1-214

Examination (in Danish)

Examination requirements (ps file or pdf file)


This page is maintained by Uffe Kjærulff.
Last updated 6 June 2002.