Edit mlp-layers.svg
| Date | Author | Comment |
|---|---|---|
| 2026-07-15 12:37:13 6b31d5 | lugonthier | feat: Update "Decision trees and ensemble methods" module with new content and visuals - Revamped the introduction to ensemble methods, emphasizing the benefits of combining models. - Expanded sections on decision trees, bagging, and boosting, including detailed explanations and formulas. - Added new SVG diagrams illustrating the bagging process, the transition from stumps to trees, and variance reduction. - Introduced new images for AdaBoost rounds and variance reduction to enhance understanding. |
| 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 17:23:32 a3ddd0 | lugonthier | Refactor Machine Learning module structure and content - Swapped the order of "Réseaux de neurones multi-couches" and "Régularisation et inférence en grande dimension" in the main Machine Learning index. - Updated references in "Régression linéaire" to point to the correct module for regularization. - Changed the next module reference in "Classification linéaire" to "Régularisation et inférence en grande dimension". - Added new module "Régularisation et inférence en grande dimension" with detailed explanations of ridge and lasso regression, including their mathematical formulations and implications for model selection. - Included visual aids for L1 and L2 regularization paths. - Introduced new module "Réseaux de neurones multi-couches" covering the architecture and training of multi-layer neural networks, emphasizing the importance of non-linearity and activation functions. - Added visual representations for neural network layers and backpropagation process. |
| 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. |
