reaks = 4)
ames_train  &lt;- training(ames_split)
ames_test   &lt;- testing(ames_split)

lm_fit      &lt;- fit_data(Sale_Price ~ Gr_Liv_Area, 
                        model = lm_spec, 
                        data = ames_train)

price_pred  &lt;- lm_fit %&gt;% 
  predict(new_data = ames_test) %&gt;% 
  mutate(price_truth = ames_test$Sale_Price)

rmse(price_pred, truth = price_truth, estimate = .pred)
```

---
class: middle, inverse

.left-column[
# A bit messy, no?
]

.right-column[

```r
set.seed(100) # Im