MACHINE LEARNING AND DATA ANALYSIS

MACHINE LEARNING AND DATA ANALYSIS

_
iten
Code
86798
ACADEMIC YEAR
2020/2021
CREDITS
6 credits during the 1st year of 11160 COMPUTER ENGINEERING (LM-32) GENOVA

6 credits during the 3nd year of 8766 Mathematical Statistics and Data Management (L-35) GENOVA

6 credits during the 1st year of 10852 COMPUTER SCIENCE (LM-18) GENOVA

SCIENTIFIC DISCIPLINARY SECTOR
ING-INF/05
LANGUAGE
English
TEACHING LOCATION
GENOVA (COMPUTER ENGINEERING )
semester
1° Semester
Teaching materials

OVERVIEW

In the information age any system or device generates some form of data for diagnostic purposes or analysis. The course details the basic techniques for collecting, processing and analyzing data in order to extract useful information and knowledge for decision making.

AIMS AND CONTENT

LEARNING OUTCOMES

Students will be provided with advanced skills related to data analysis. Students will learn insights on data mining methodologies and specific applications of these methodologies to particular data organization.

AIMS AND LEARNING OUTCOMES

The student will be able to apply the acquired skills to a case study by deriving the model of the phenomenon that generated the data under analysis.

Teaching methods

The course consists of lectures and practical lab sessions using MATLAB.

SYLLABUS/CONTENT

  1. Introduction
  2. Data, Uncertainty and Learning Problems
  3. ​Data preprocessing and Exploratory Data Analysis
  4. Association Mining
  5. Statistical inference
  6. Naïve methods
  7. Rule based methods
  8. Linear methods
  9. Kernel methods
  10. Advances in kernel methods
  11. Neural networks

RECOMMENDED READING/BIBLIOGRAPHY

C.C.Aggarwal, "Data Mining - The textbook", 2015

T.Hastie, R.Tibshirani, J.Friedman, "The Elements of Statistical Learning: Data Mining, Inference, and Prediction", 2009.

M.R.Berthold, C.Borgelt, F.Hoppner, F.Klawonn, "Guide to Intelligent Data Analysis", 2010.

TEACHERS AND EXAM BOARD

Ricevimento: By appointment.

Ricevimento: The meetings must be scheduled by email with the teacher.

Exam Board

LUCA ONETO (President)

MARCO MARATEA

DAVIDE ANGUITA (President Substitute)

LESSONS

Teaching methods

The course consists of lectures and practical lab sessions using MATLAB.

ORARI

L'orario di tutti gli insegnamenti è consultabile su EasyAcademy.

EXAMS

Exam description

Oral

Exam schedule

Date Time Location Type Notes
30/07/2021 09:00 GENOVA Esame su appuntamento
01/09/2021 08:00 GENOVA Esame su appuntamento Exam be scheduled by email with luca.oneto@unige.it Please carefully read the instructions on AulaWeb
01/09/2021 08:00 GENOVA Orale Exam be scheduled by email with luca.oneto@unige.it Please carefully read the instructions on AulaWeb
16/09/2021 09:00 GENOVA Esame su appuntamento