Machine Learning and Data Mining

This teaching unit will be held in class, i.e. face to face.

Introduction to Data Mining perspective; Association rules; Decision trees; Instance-based learning (nearest neighbors); Clustering; Support Vector machines (SVM); Evaluation (Train & Test, Cross-validation, Leaving-one-out); Data Streams.

Details

Code 32032
62032
Type Course
ECTS 5
Site Neuchâtel
Track(s) T3 – Advanced Information Processing
T6 – Data Science
Semester A2020

Teaching

Learning Outcomes

The main objectives of this course is to introduce the students to the various techniques and strategies that can be used to

  1. to discover pertinent relationships (or correlations) between variables
  2. to evaluate such relationships and machine learning approaches
  3. to know how to conduct a machine learning process based on available data and to interpret the results.

Practical exercises will complete the theoretical presentation.

Lecturer(s) Marcelo Pasin
Language english
Course Page

The course page in ILIAS can be found at https://ilias.unibe.ch/goto_ilias3_unibe_crs_1841349.html.

Schedules and Rooms

Period Weekly
Schedule Monday, 08:15 - 12:00
Location UniNE, Unimail
Room B013

Additional information

Comment

First Lecture
The first lecture will take place on Monday, 14.09.2020 at 08:15 in UniNE, Unimail, room B013.