small typo in JSMA tutorial md
spotted by
@@ -147,7 +147,7 @@ adv_x = apply_perturbations(i, j, adv_x, increase, theta, clip_min, clip_max)
In the first stage of the process, we compute the Jacobian component
corresponding to each pair of output class and input feature. This
-helps us estimating how changes in the input features (here pixels
+helps us estimate how changes in the input features (here pixels
of the MNIST images) will affect each of the class probability
assigned by the model. The Jacobian is a 10 x 28 x 28 matrix of floating
point numbers where large positive values mean that increasing the
