Evaluating the Performance of Machine Learning Models

Описание: Evaluating the Performance of Machine Learning Models – Complete Guide
In this video, we’ll explore how to measure and evaluate the performance of Machine Learning models.
Model evaluation is one of the most important steps in building reliable AI systems — it tells us how well our model is working and whether it will generalize to new data.
You’ll learn:
Why evaluation is important in ML
Key performance metrics for classification (Accuracy, Precision, Recall, F1-Score)
Performance metrics for regression (MSE, RMSE, MAE, R²)
Confusion Matrix explained with examples
Real-world examples of when to use which metric