Onderwijs Informatica en Informatiekunde

Vak-informatie Informatica en Informatiekunde

Pattern recognition

Website:

Course code:

INFOMPR

Credits:

7.5 ECTS

Period:

period 2 (week 46 through 5, i.e., 9-11-2020 through 5-2-2021; retake week 16)

Timeslot:

Participants:

Schedule:

Official schedule representation can be found in MyTimetable

Teachers:

Note:

No up-to-date course description available.
Text below is from year 2019/2020

Contents:

Knowledge of elementary probability theory, statistics, multivariable calculus and linear algebra is presupposed.

In this course we study statistical pattern recognition and machine learning.

The subjects covered are:

General principles of data analysis: overfitting, bias-variance trade-off, model selection, regularization, the curse of dimensionality.
Linear statistical models for regression and classification.
Clustering and unsupervised learning.
Support vector machines.
Neural networks and deep learning.

For questions about enrollment, registration, waiting lists, admittance, etc. please contact the student desk at science.gsns@uu.nl.

Literature:

May change!

Book: Christopher M. Bishop, Pattern Recognition and Machine Learning, Springer, 2006.
Book: Ian Goodfellow, Yoshua Bengio and Aaron Courville, Deep Learning, MIT Press, 2016.
Book URL: http://www.deeplearningbook.org.
Possibly additional literature in the form of research papers, book chapters, etc.

Course form:

Lectures and computer lab sessions.

Exam form:

Written exam and practical assignments.

Minimum effort to qualify for 2nd chance exam:

To qualify for the retake exam, the grade of the original must be at least 4.

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