$$`

gradient descent:
$$\hat{y}_{j+1} = \hat{y}_j - \gamma \frac{\partial L(y_i, \hat{y}_i)}{\partial\hat{y}}$$
]
---
#GradientBoostingRegressor

.center[
![:scale 50%](images/grad_boost_regression_steps.png)
]
???
Here's an illustration for doing this for regression. This
is a 1D regression dataset for illustration purposes here to
form features on the x-axis, the prediction is on the
y-axis.


In the first step, I'm just fitting my tree to the data. I
use a simple tree of depth 3. The depth 3 tree is not