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Data Science Academy · Lesson

Regression Metrics: MAE, MSE, R2

Measuring numeric prediction error.

Why Measure Error

When a model predicts numbers, you need one honest score for how far off it is. That score is an error metric, your truth-teller. 📏

The Residual Idea

Start with the residual: the gap between the true value and the predicted one. Every regression metric is just a way to summarize these gaps.

residual = y_true - y_pred

All lessons in this course

  1. Regression Metrics: MAE, MSE, R2
  2. The Confusion Matrix Decoded
  3. Precision, Recall, and F1
  4. ROC, AUC, and Thresholds
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