| Figure 6.1 - Key steps of the machine learning workflow.png | 38.1 KB | |
| Figure 6.10 - Train, validation, and hold-out test set.png | 22 KB | |
| Figure 6.11 - Validation and learning curves.png | 89.7 KB | |
| Figure 6.2 - In-sample regression errors.png | 272.2 KB | |
| Figure 6.3 - Confusion matrix and related error metrics.png | 22.9 KB | |
| Figure 6.4 - Receiver-Operating Characteristics, Precision-Recall Curve, and F1 Scores charts.png | 167 KB | |
| Figure 6.5 - Pairwise scatter plots of outcome and features.png | 95.1 KB | |
| Figure 6.6 - A visual example of overfitting with polynomials.png | 138.9 KB | |
| Figure 6.7 - Errors and out-of-sample predictions for polynomials of different degrees.png | 300.2 KB | |
| Figure 6.8 - Learning curves and bias-variance tradeoff.png | 197 KB | |
| Figure 6.9 - Training and test set.png | 11.5 KB | |
