 errors (the squared part).

---
name: overfitting
layout: false
# Model accuracy
## Overfitting

Low MSE on the data that trained the model is not necessarily impressive — maybe the model is just **overfitting** our data.

**Tradeoff:** More flexible models...

- might better fit complex systems (lower bias).

- but also might falsely interpret noise as signal (higher variance).

---
name: training-testing

# Model accuracy
## Training vs. testing data

**Our real goal:** A model that performs well *on d