Please note that Code+Figures links are coming soon.
| Chapter | Name | Colab for figures | Other material |
|---|---|---|---|
| 1 | Introduction | Code only | Links |
| Part I : Foundations | |||
| 2 | Probability: univariate models | Code only | Links |
| 3 | Probability: multivariate models | Code only | Links |
| 4 | Statistics | Code only | Links |
| 5 | Decision theory | Code only | Links |
| 6 | Information theory | Code only | Links |
| 7 | Linear algebra | Code only | Links |
| 8 | Optimization | Code only | Links |
| Part II : Linear models | |||
| 9 | Linear discriminant analysis | Code only | Links |
| 10 | Logistic regression | Code only | Links |
| 11 | Linear regression | Code only | Links |
| 12 | Generalized linear models | Code only | Links |
| Part III : Deep neural networks | |||
| 13 | Neural networks for unstructured data | Code only | Links |
| 14 | Neural networks for images | Code only | Links |
| 15 | Neural networks for sequences | Code only | Links |
| Part IV : Nonparametric models | |||
| 16 | Exemplar-based methods | Code only | Links |
| 17 | Kernel methods | Code only | Links |
| 18 | Trees, forests, bagging and boosting | Code only | Links |
| Part V : Beyond supervised learning | |||
| 19 | Learning with fewer labeled examples | Code only | Links |
| 20 | Dimensionality reduction | Code only | Links |
| 21 | Clustering | Code only | Links |
| 22 | Recommender systems | Code only | Links |
| 23 | Graph embeddings | Code only | Links |