Deep learning et advanced machine learning
- UE code INFOM232
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Schedule
30 15Quarter 1
- ECTS Credits 5
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Language
Anglais
- Teacher Frenay Benoît
At the end of the course, the student must demonstrate an understanding of the different topics covered (see content), i.e., be able to express in his own words the theory and methods seen in the course and explain in which context they are useful. He must also be able to implement the techniques seen during a complex data analysis problem.
As an extension of the IDASM102 "Machine learning and data mining" course, this course explores more advanced methods in machine learning and deep learning. The following topics will be discussed:
These courses will be complemented by two "research talks" sessions based on live interventions by scientific experts and international conferences recorded and viewed during the lesson. A session will also be devoted to the presentation of projects (see "evaluation mode").
The course is divided into two learning activities. The first consists of lectures and is evaluated by an oral examination on the theory of the course (70% of the overall course mark). The second is an ongoing assessment of students' ability to implement and document the techniques seen in class (30% of the overall course mark). To do this, he will have to carry out a project whose approximate timing is:
The project will be evaluated on the basis of regular submissions on an online platform and the final presentation. It will be carried out in teams of two students.
References are given during the course.
Training | Study programme | Block | Credits | Mandatory |
---|---|---|---|---|
Master 60 en sciences informatiques | Standard | 0 | 5 | |
Master 120 en sciences informatiques, à finalité spécialisée en data science | Standard | 0 | 5 | |
Master 120 en sciences informatiques, à finalité spécialisée en software engineering | Standard | 0 | 5 | |
Master 60 en sciences informatiques | Standard | 1 | 5 | |
Master 120 en sciences informatiques, à finalité spécialisée en data science | Standard | 2 | 5 | |
Master 120 en sciences informatiques, à finalité spécialisée en software engineering | Standard | 2 | 5 |