Course Introduction
Machine Learning and Data Mining

Machine Learning and Data Mining 2
Prof. Pier Luca Lanzi
Dipartimento di Elettronica e Informazione
pierluca.lanzi@polimi.it
tel. 02 23993472
http://webspace.elet.polimi.it/lanzi
Office Hours
Wednesday, from 15:00 until 17:00
Prof. Pier Luca Lanzi

Course Structure 3
Basic Introduction (24 hours)
Short introduction to Data Mining and to the most relevant
Machine Learning techniques that are applied in Data Mining
Advaced Techniques and Applications (16 hours)
Advanced Machine Learning techniques and
Data Mining applications
Final Project
An application to real-world data
Prof. Pier Luca Lanzi

Tecniche di Apprendimento Automatico 4
per Applicazioni di Data Mining
This shorter course is covered by the first 20 hours
The topics are more or less the ones covered by
the previous editions
Lectures are in English
Final test is in Italian (in English upon request)
Prof. Pier Luca Lanzi

Course Outline 5
Knowledge Discovery, Data Mining, and Machine Learning
The representation of data and knowledge
Typical Data Mining tasks
Associations
Clustering
Classification
Aggregate methods
Preprocessing
Advanced techniques and applications
Prof. Pier Luca Lanzi

Evaluation 6
One written exam
Course project
Prof. Pier Luca Lanzi

Course Material 7
Lecture slides available at http://webspace.elet.polimi.it/lanzi
Bibliography
Jiawei Han, Micheline Kamber.
“Data Mining: Concepts and Techniques” Morgan Kauffman, 2000.
Tom Mitchell. “Machine Learning”, McGraw Hill 1997
Ian H. Witten, Eibe Frank. “Data Mining: Practical Machine Learning
Tools and Techniques with Java Implementations” 2nd Edition.
Software
Weka, http://www.cs.waikato.ac.nz/~ml/weka/
Prof. Pier Luca Lanzi