Below you will find an index of the models implemented in this repository, complete with direct links to the code in both Python (🐍) and Julia (📊).
| Model Name | Category | Python Code | Julia Code |
|---|---|---|---|
| k-Nearest Neighbors | Classification | ❌ | 📊 |
| Linear Least Squares | Regression | ❌ | ❌ |
| Ridge Regression | Regression | ❌ | ❌ |
| Lasso | Regression | ❌ | ❌ |
| Support Vector Machines | Classification | ❌ | ❌ |
| Random Forests | Ensemble Methods | ❌ | ❌ |
| Boosting | Ensemble Methods | ❌ | ❌ |
| Gradient Boosting | Ensemble Methods | ❌ | ❌ |
| Principal Component Analysis (PCA) | Dimensionality Reduction | ❌ | ❌ |
| Kernel PCA | Dimensionality Reduction | ❌ | ❌ |
| Multiple Discriminant Analysis (MDA) | Dimensionality Reduction | ❌ | ❌ |
| Isomap | Manifold Learning | ❌ | ❌ |
| t-Distributed Stochastic Neighbor Embedding (t-SNE) | Manifold Learning | ❌ | ❌ |
| k-Means Clustering | Clustering | ❌ | ❌ |