Reda Khoufache
PhD candidate | Machine learning scientist
PhD candidate | Machine learning scientist
Outils mathématiques (M1):
Support du cours à jour (jusqu'à la séance du 05 Décembre 2025): Polycopié
Slides (Clustering et modèles de mélange): Slides
Travaux dirigés:
TD 1 et 2 (Algèbre linéaire et projection orthogonale) : TD 1 et 2
TD 3 (Vecteurs aléatoires et gaussiens) : TD 3
TD 4 (Espérance conditionnelle) : TD 4
TD 5 (TP Clustering et modèles de mélange): TD 5
Contrôles continues:
Mathématiques générales (L1):
Contrôles continues
Machine learning (M2):
Introduction and Python refresher: Slides | Practical | Correction
Linear Algebra: Slides | Practical | Correction
Probability Theory: Slides | Practical | Correction
Descriptive Statistics: Slides | Practical | Correction
Numerical Optimization: Slides | Practical | Correction
Supervised Learning: Slides | Practical | Correction
Deep neural networks: Slides | Practical | Correction
Convolutional neural networks: Slides
Unsupervised learning: Slides
Data challenge:
Link: https://challengedata.ens.fr/professors/challenges/161/
Course code: Big Data Analytics 25
Deadline: 31/05/2025
What is required to submit:
Your notebook for preprocessing the data, training your final model, and generating predictions;
Your 3-page (final) PDF-LaTeX report describing:
The data preprocessing steps;
The model selection phase.
Your final model and its performance scores.
The challenges you encountered and your achievements.
Your report should also contain your ID.