Accuracy vs Precision vs Recall: Model Evaluation Explained

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.