 | Study programme 2021-2022 | Français | |
| Machine Learning I | |||
Learning Activity |
| Code | Lecturer(s) | Associate Lecturer(s) | Subsitute Lecturer(s) et other(s) | Establishment |
|---|---|---|---|---|
| S-INFO-256 |
|
|
| Language of instruction | Language of assessment | HT(*) | HTPE(*) | HTPS(*) | HR(*) | HD(*) | Term |
|---|---|---|---|---|---|---|---|
| Anglais, Français | Anglais, Français | 30 | 30 | 0 | 0 | 0 | Q2 |
Content of Learning Activity
The course introduces statistical and machine learning methods for predictive modelling based on big datasets. The unit covers, among other topics, linear and non-linear methods for regression, classification, clustering and dimensionality reduction.
Required Learning Resources/Tools
Not applicable
Recommended Learning Resources/Tools
Not applicable
Other Recommended Reading
Not applicable
Mode of delivery
- Mixed
Type of Teaching Activity/Activities
- Cours magistraux
- Travaux pratiques
Evaluations
The assessment methods of the Learning Activity (AA) are specified in the course description of the corresponding Educational Component (UE)
(*) HT : Hours of theory - HTPE : Hours of in-class exercices - HTPS : hours of practical work - HD : HMiscellaneous time - HR : Hours of remedial classes. - Per. (Period), Y=Year, Q1=1st term et Q2=2nd term