Spoilers

Explore how to build a binary classification model in PyTorch by understanding logits, using binary cross-entropy loss, and handling imbalanced datasets. Learn the impact of classification thresholds on evaluation metrics and how to construct ROC and precision-recall curves to assess model performance.