In this function, we have:

```
def compute_model_output(x, w, b):
"""
Computes the prediction of a linear model
Args:
x (ndarray (m,)): Data, m examples
w,b (scalar) : model parameters
Returns
y (ndarray (m,)): target values
"""
m = x.shape[0]
f_wb = np.zeros(m)
for i in range(m):
f_wb[i] = w * x[i] + b
return f_wb
```

So when he asks about this

are we trying to manipulate w and b to get f(x) as close to the known y targets? when I printed the tm-_fwb variable they are the same outputs(targets) as y_train. So is this how we do the math portion of it?