Edit forest-vs-tree.png

Date Author Comment
2026-07-28 13:29:31  81a3ca lugonthier slide 01
2026-07-10 12:03:30  0ad9b6 lugonthier Remove "07 Regularization and high-dimensional inference" chapter and add "07 Support Vector Machines" and "08 Decision trees and ensemble methods" chapters with corresponding images.
2026-07-02 16:43:49  17beab lugonthier Add French translations for Regularization, Support Vector Machines, and Decision Trees modules - Created "08 Regularization and high-dimensional inference.md" with detailed explanations on regularization techniques including ridge, lasso, and elastic net. - Added images for L1 and L2 geometry and regularization path. - Created "09 Support Vector Machines.md" covering SVM concepts, including margin, loss functions, kernels, and duality. - Added images for SVM margin and kernel decision boundaries. - Created "10 Decision trees and ensemble methods.md" explaining decision trees, random forests, and boosting techniques. - Added images for decision tree boundaries and forest vs tree comparison.
2026-07-02 15:52:15  e0287e lugonthier Add new content and images for machine learning and mathematics modules - Added images for regularization and high-dimensional inference. - Introduced Support Vector Machines (SVM) module with detailed explanations and images. - Created Decision Trees and Ensemble Methods module with comprehensive content and illustrations. - Added a Mathematics overview module and a refresher on mathematical concepts essential for machine learning. - Included SVG diagrams for Bayes' rule and multivariate Gaussian distribution.
2026-07-02 14:39:19  36084c lugonthier 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.
2026-06-30 12:04:21  1c3139 Lucas Gonthier 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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