Machine Learning and Data Mining: 00 Course Introduction

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

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Machine Learning and Data Mining: 00 Course Introduction

by Pier Luca Lanzi on Mar 14, 2007

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