Deep Learning - blame (12d21f)

Blame

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.

# Deep Learning

Neural networks from the single perceptron to modern transformers: how depth, the right activations, and gradient-based training let a model learn its own features instead of hand-crafted ones.

12d21f	lugonthier	2026-07-24 11:49:19
Remove unused SVG files and update Markdown content for clarity and accuracy in MLOps and Machine Learning modules. Adjust references to optimization techniques and activation functions, and enhance explanations in the mathematical refresher section.

**Prerequisites:** the [Machine Learning](/en/Machine%20Learning) course, especially [Multilayer neural networks](/en/Machine%20Learning/06%20Multilayer%20neural%20networks), which builds the model and covers the losses and backpropagation used throughout this course. Basic Python, calculus, and linear algebra.

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.

## Syllabus

1. [Introduction](/en/Deep%20Learning/01%20Introduction)

12d21f	lugonthier	2026-07-24 11:49:19
Remove unused SVG files and update Markdown content for clarity and accuracy in MLOps and Machine Learning modules. Adjust references to optimization techniques and activation functions, and enhance explanations in the mathematical refresher section.

2. [Activation functions](/en/Deep%20Learning/02%20Activation%20functions)

3. [Optimization](/en/Deep%20Learning/03%20Optimization)

4. [Training deep networks](/en/Deep%20Learning/04%20Training%20deep%20networks)

5. [Convolutional networks](/en/Deep%20Learning/05%20Convolutional%20networks)

6. [Embeddings and representation learning](/en/Deep%20Learning/06%20Embeddings%20and%20representation%20learning)

7. [Recurrent networks](/en/Deep%20Learning/07%20Recurrent%20networks)

8. [LSTM and GRU](/en/Deep%20Learning/08%20LSTM%20and%20GRU)

9. [Attention](/en/Deep%20Learning/09%20Attention)

10. [Transformers](/en/Deep%20Learning/10%20Transformers)

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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