NWI-NM048B
Advanced Machine Learning
Course infoSchedule
Course moduleNWI-NM048B
Credits (ECTS)6
CategoryMA (Master)
Language of instructionEnglish
Offered byRadboud University; Faculty of Science; Wiskunde, Natuur- en Sterrenkunde;
Lecturer(s)
Coordinator
prof. dr. H.J. Kappen
Other course modules lecturer
Lecturer
prof. dr. H.J. Kappen
Other course modules lecturer
Contactperson for the course
prof. dr. H.J. Kappen
Other course modules lecturer
Examiner
prof. dr. H.J. Kappen
Other course modules lecturer
Academic year2021
Period
KW2-KW3  (08/11/2021 to 10/04/2022)
Starting block
KW2
Course mode
full-time
Remarks-
Registration using OSIRISYes
Course open to students from other facultiesYes
Pre-registrationNo
Waiting listNo
Placement procedure-
Aims
The aim of the course is to provide the student with a advanced concepts of modern machine learning at the international research level. The student will become familiar with the modern literature by presenting recent research papers on various topics. The student will implement these methods in computer code and apply them to real learning problems. See http://www.snn.ru.nl/~bertk/machinelearning/adv_ml.html for details.
Content
The course provides advanced topics in machine learning. The course is intended for Master's students in physics and mathematics.
This course is the follow-up of the course Machine Learning, which is part of the Computational Data Science minor. The course provides a good preparation for a Masters' specialisation in Theoretical Neuroscience or Machine Learning. See http://www.snn.ru.nl/~bertk/machinelearning/adv_ml.html for details.
Level

Presumed foreknowledge
The following course is required: CDS: Machine Learning
Test information
Examination is weighted average of homework assignments and presentations.http://www.snn.ru.nl/~bertk/machinelearning
Specifics
 
Required materials
Book
David MacKay, Information Theory, Inference and Learning Algorithms, Cambridge University press. The entire book can be viewed on-screen at http://www.inference.phy.cam.ac.uk/mackay/itila/book.html
Handouts
Additional handouts and papers on the course website http://www.snn.ru.nl/~bertk/machinelearning/adv_ml.html

Instructional modes
Course occurrence

Lecture

Tutorial

Tests
assignments
Test weight1
OpportunitiesBlock KW3, Block KW4