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1c3139 Lucas Gonthier 2026-06-30 12:04:21
Initial commit: course content (Machine Learning, MLOps) in EN and FR Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
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# Machine Learning
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Les fondements du machine learning : passer de données brutes à un modèle entraîné et évalué.
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**Prérequis :** Python de base, notions d'algèbre linéaire et de statistiques.
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## Programme
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1. [Introduction](/fr/Machine%20Learning/01%20Introduction)
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2. [Concepts généraux](/fr/Machine%20Learning/02%20General%20concepts)
36084c lugonthier 2026-07-02 14:39:19
Add new content and images for Linear Models, Regularization, SVMs, and Decision Trees - Added images for linear regression, logistic regression, and perceptron. - Introduced a new section on Regularization and High-Dimensional Inference with detailed explanations and images. - Added content on Support Vector Machines, including definitions, loss functions, and kernel methods. - Created a new section on Decision Trees and Ensemble Methods, covering CART, bagging, random forests, and boosting. - Included relevant images to illustrate concepts in Decision Trees and Ensemble Methods.
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3. [Évaluation et validation des modèles](/fr/Machine%20Learning/03%20Model%20evaluation%20and%20validation)
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4. [Modèles linéaires](/fr/Machine%20Learning/04%20Linear%20models)
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5. [Régularisation et inférence en grande dimension](/fr/Machine%20Learning/05%20Regularization%20and%20high-dimensional%20inference)
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6. [Machines à vecteurs de support](/fr/Machine%20Learning/06%20Support%20Vector%20Machines)
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7. [Arbres de décision et méthodes d'ensemble](/fr/Machine%20Learning/07%20Decision%20trees%20and%20ensemble%20methods)
1c3139 Lucas Gonthier 2026-06-30 12:04:21
Initial commit: course content (Machine Learning, MLOps) in EN and FR Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
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1a0e72 lugonthier 2026-07-01 15:43:09
Update navigation links for consistency in English and French MLOps and Machine Learning documents
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[MLOps](/fr/MLOps) · [Accueil](/fr)