CDS: Machine Learning
Master course, Radboud University, 2025
CDS: Machine Learning (NWI-NM048D)
- Master course - 3 EC
- Teaching Assistants: Eduardo Dominguez, Mauricio Diaz-Ortiz
This course is intended for Master’s students in physics and mathematics as well as master’s students in artificial intelligence/computer science with sufficient mathematical background.
Main topics
- Probabilistic approach to machine learning (Bayesian inference, evidence framework for model comparison)
- Learning and generalization in classification problems (perceptrons)
- Gradient descent methods in machine learning and neural networks
- Deep neural networks
- Inference and learning in graphical models
Course Material
Each lecture comes with an interactive jupyter notebook. Find the notebooks at this repo.
Books
- Information Theory, Inference and Learning Algorithms by David MacKay.
- Machine Learning: a probabilistic perspective by Kevin Murphy.
Schedule
| Week | Topic | Material | |
|---|---|---|---|
| 1 | 36 | Probability, entropy and inference | MacKay Chapter 2 + notebooks 1.1, 1.2 |
| 2 | 37 | Model comparison | MacKay Chapter 3, 27, 28 + notebooks 2.1, 2.2 |
| 3 | 38 | Perceptrons | notebook 3 |
| 4 | 39 | Learning algorithms | notebook 4.1, 4.2 |
| 5 | 40 | Deep learning | notebook 5 |
| 6 | 41 | Graphical models | Murphy Chapter 10 + notebook 6 |
| 7 | 42 | Mixture models and Expectation Maximization | Murphy Chapter 11 + notebook 7 |
Tutorial schedule
Tutorials will be both in person and online. For the online tutorials, join the Discord server.
| Week | Tue | Wed | Thu | |
|---|---|---|---|---|
| 1 | 36 | Lec 1: Ex 1 assigned | Lec 2: Ex 2 assigned | |
| 2 | 37 | Tut 1: work on Ex 1 and Ex 2 | Tut 2: work on Ex 1 and Ex 2 | |
| 3 | 38 | Lec 3: Ex 3 assigned | Ex 1, 2 due | Tut 3: Ex 1, 2 discussed - work on Ex 3 |
| 4 | 39 | Lec 4: Ex 4 assigned | Ex 3 due | Tut 4: Ex 3 discussed - work on Ex 4 |
| 5 | 40 | Lec 5: Ex 5 assigned | Ex 4 due | Tut 5: Ex 4 discussed - work on Ex 5 |
| 6 | 41 | Lec 6: Ex 6 assigned | Ex 5 due | Tut 6: Ex 5 discussed - work on Ex 6 |
| 7 | 42 | Lec 7: Ex 7 assigned | Ex 6 due | Tut 7: Ex 6 discussed - work on Ex 7 |
| 8 | 43 | Ex 7 due | Bonus Tut: online discussion of Ex 7 |
Exam
There will be no final examination. The students will work in groups of maximum 3 persons. The grade will be the average of homework assignments. Each student gets the grade of their group.