Advanced Topics in Machine Learning
People
Description
COURSE OBJECTIVES
The goal of the course is to expose students to advanced topics in machine learning so as to complement and enrich material seen in basic machine learning courses.
COURSE DESCRIPTION
The course aims at entertaining students on advanced topics in machine learning by both touching technologies/methodologies and applications.
LEARNING METHODS
The teaching modality blends frontal teaching done by the instructors -we will also invite international fellows to deliver some lectures- and presentations done by groups of students on hot machine learning topics on provided material. Assignments will be given to groups of students to perfect some topics understanding.
EXAMINATION INFORMATION
Assignments and presentations done by the students.
PREREQUISITES
Deep Learning Lab, Machine Learning
REFERENCES
Material and papers provided by the instructor
Education
- Master of Science in Artificial Intelligence, Elective course, 1st year
- Master of Science in Artificial Intelligence, Elective course, 2nd year
- Master of Science in Computational Science, Elective course, 1st year
- Master of Science in Computational Science, Elective course, 2nd year
- Master of Science in Informatics, Elective course, 1st year
- Master of Science in Informatics, Elective course, 2nd year
- PhD programme of the Faculty of Informatics, Elective course, Lecture, 1st year (2.0 ECTS)
- PhD programme of the Faculty of Informatics, Elective course, Lecture, 2nd year (2.0 ECTS)
