Update app.py

app.py

@@ -111,9 +111,9 @@ def gradient_descent(n_samples=100, intercept=4, slope=3, intercept_random=4, sl
               shuffled_indices = np.random.permutation(len(X))
               X_b_shuffled = X[shuffled_indices]
               y_shuffled = y[shuffled_indices]
-              for b in range(0, len(X), minibatch_size):
-                  X_mini = X_b_shuffled[b:b+minibatch_size]
-                  y_mini = y_shuffled[b:b+minibatch_size]
+              for k in range(0, len(X), minibatch_size):
+                  X_mini = X_b_shuffled[k:k+minibatch_size]
+                  y_mini = y_shuffled[k:k+minibatch_size]
                          
                   b_grad = 0.0
                   w_grad = 0.0