Teaching (2023 - 2024)
- Master 1: Agility
- Lecture: PDF file
- Pratical works:
- Master 1: Machine learning
- Lecture: PDF file
- Tutorials:
- TD1: Decision tree
- Pratical works:
- TP0: Python for ML introduction
- TP1: Linear and Polynomial regression
- TP2: KNN
- TP3: K-means
- TP4: Upper Confidence Bound
- TP5: Q-learning
- TP6: Gradient descent
- TP7: Neural Network
- TP8: Convolutional Neural Network
- Projects:
- Intermediate: supervised learning
- Final project: advanced ML problem)
- BUT3: Deep learning
- Lecture: PDF file
- Pratical works:
- TP1: Gradient descent
- TP2: Deep Neural Network
- TP3: Convolutional Neural Network
- TP4: AutoEncoder
- Projects:
- Final project: advanced ML problem
- Other resources:
- Configure Python: virtual environment
- Python: OOP and library main concepts