Moving course1 to course1 subdir.

machine_learning/course1/mlclass-ex4-008/mlclass-ex4/sigmoidGradient.m

@@ -0,0 +1,23 @@
+function g = sigmoidGradient(z)
+%SIGMOIDGRADIENT returns the gradient of the sigmoid function
+%evaluated at z
+%   g = SIGMOIDGRADIENT(z) computes the gradient of the sigmoid function
+%   evaluated at z. This should work regardless if z is a matrix or a
+%   vector. In particular, if z is a vector or matrix, you should return
+%   the gradient for each element.
+
+g = zeros(size(z));
+
+% ====================== YOUR CODE HERE ======================
+% Instructions: Compute the gradient of the sigmoid function evaluated at
+%               each value of z (z can be a matrix, vector or scalar).
+
+e = exp(-1*z);
+g = e ./ ((e+1).^2);
+
+% =============================================================
+
+
+
+
+end