Accuracy vs Precision vs Recall: Model Evaluation Explained

Описание: How do you know if your machine learning model is really performing well?

In this video, we explain the three core evaluation metrics:
Accuracy – overall correctness of predictions
Precision – how reliable positive predictions are
Recall – how many real positives your model catches

Learn why accuracy can be misleading (especially with imbalanced data), and how to balance precision vs recall depending on your use case.