diff --git a/examples/utils/dataset.py b/examples/utils/dataset.py
index 1c48eaf..3d9d553 100644
--- a/examples/utils/dataset.py
+++ b/examples/utils/dataset.py
@@ -70,7 +70,7 @@ def load_mnist_realval(path, one_hot=True, dequantify=False):
                          '/mnist.pkl.gz', path)
 
     f = gzip.open(path, 'rb')
-    train_set, valid_set, test_set = pickle.load(f)
+    train_set, valid_set, test_set = pickle.load(f, encoding='latin1')
     f.close()
     x_train, t_train = train_set[0], train_set[1]
     x_valid, t_valid = valid_set[0], valid_set[1]
@@ -172,16 +172,16 @@ def load_cifar10(path, normalize=True, dequantify=False, one_hot=True):
     train_x, train_y = [], []
     for i in range(1, 6):
         batch_file = os.path.join(batch_dir, 'data_batch_' + str(i))
-        with open(batch_file, 'r') as f:
-            data = pickle.load(f)
+        with open(batch_file, 'rb') as f:
+            data = pickle.load(f, encoding='latin1')
             train_x.append(data['data'])
             train_y.append(data['labels'])
     train_x = np.vstack(train_x)
     train_y = np.hstack(train_y)
 
     test_batch_file = os.path.join(batch_dir, 'test_batch')
-    with open(test_batch_file, 'r') as f:
-        data = pickle.load(f)
+    with open(test_batch_file, 'rb') as f:
+        data = pickle.load(f, encoding='latin1')
         test_x = data['data']
         test_y = np.asarray(data['labels'])