Faculteit  Science and Engineering 
Jaar  2020/21 
Vakcode  WBCS03205 
Vaknaam  Introduction to Machine Learning 
Niveau(s)  bachelor 
Voertaal  Engels 
Periode  semester I a 
ECTS  5 
Rooster  rooster.rug.nl 
Uitgebreide vaknaam  Introduction to Machine Learning  
Leerdoelen  At the end of the course, the student is able to: 1. Obtain an overview of the main methods and techniques used in pattern recognition and machine learning 2. Basic problems of machine learning and pattern recognition 3. Select appropriate techniques for particular tasks 4. Implement basic learning and validation methods and apply them to practical data sets. 5. Obtain insight into some basic operations in image processing 

Omschrijving  The focus of this course is to introduce the concepts of machine learning, including unsupervised and supervised learning. Unsupervised learning covers dimensionality reduction, clustering, and densitybased estimation methods. Supervised learning is explained mainly in terms of classification problems, with emphasis on distancebased methods such as Learning Vector Quantization as an example framework. Validation methods and the problem of overfitting are briefly discussed in terms of classification and regression problems. Methods are also illustrated by practical applications.  
Uren per week  
Onderwijsvorm  Hoorcollege (LC), Practisch werk (PRC)  
Toetsvorm 
Practisch werk (PR), Schriftelijk tentamen (WE)
(Final grade: weighted average of the marks for the practicals (60%) and the written (digital) exam (40%). In order to pass, students must get a mark of at least 5.5 for both of these separately, and the weighted average has to be at least 5.75. Weighted averages above 4.75 and below 5.75 will result in a final grade 5.0, in all other cases the grade is rounded to the nearest halfinteger value.) 

Vaksoort  bachelor  
Coördinator  prof. dr. M. Biehl  
Docent(en)  prof. dr. M. Biehl ,dr. E. Talavera Martínez  
Verplichte literatuur 


Entreevoorwaarden  Basic programming skills, knowledge of mathematics and statistics that is typical of the respective courses included in standard bachelor CS curricula.  
Opmerkingen  The computer practicals are in Matlab. It would be helpful if students have some programming experience in Matlab. Otherwise, they should quickly acquire some Matlab programming skills by following an online tutorial (many are available on internet). This is not difficult because Matlab is easy to learn on the background of some programming skills in another programming language. The use of matlab will not be obligatory, students can resort to Python if they wish.  In the academic year 20202021, all CS bachelor courses have limited enrollment:  CS students can always enter each course, regardless of whether the course is mandatory for them or not.  A maximum of only 20 places per course is available for nonCS students. These places are filled on a firstcomefirstserved basis, with priority given to students with a strong CSrelated background (e.g., CS exchange students, AI students, etc.). These students need to meet the course prerequisite requirements as mentioned on Ocasys. For more info about the enrollment procedure, see https://student.portal.rug.nl/infonet/studenten/fse/programmes/bsccs/general/vakintekeningprocedure#cap 

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