diff --git a/examples/example_sine.rs b/examples/example_sine.rs
index 87ef3d7..516580f 100644
--- a/examples/example_sine.rs
+++ b/examples/example_sine.rs
@@ -21,8 +21,8 @@ fn main() {
         Uniform::new(training_interval.0, training_interval.1),
     )
     .to_vec();
-    let mut x_train = Vec::new();
-    let mut y_train = Vec::new();
+    let mut x_train = Vec::with_capacity(steps);
+    let mut y_train = Vec::with_capacity(steps);
     for x in training_values {
         x_train.push(Array1::from_elem(1usize, x));
         y_train.push(Array1::from_elem(1usize, x.sin()));
@@ -32,8 +32,8 @@ fn main() {
     let interval_length = training_interval.1 - training_interval.0;
     let step_size = interval_length / test_steps as f64;
     let testing_values = Array1::range(training_interval.0, training_interval.1, step_size);
-    let mut x_test = Vec::new();
-    let mut y_test_true = Vec::new();
+    let mut x_test = Vec::with_capacity(test_steps);
+    let mut y_test_true = Vec::with_capacity(test_steps);
     for x in testing_values {
         x_test.push(Array1::from_elem(1usize, x));
         y_test_true.push(Array1::from_elem(1usize, x.sin()));
diff --git a/src/lib.rs b/src/lib.rs
index 2b3f2af..440b317 100644
--- a/src/lib.rs
+++ b/src/lib.rs
@@ -26,8 +26,7 @@ impl Network {
     }
 
     pub fn predict(&mut self, inputs: &[Array1<f64>]) -> Vec<Array1<f64>> {
-        assert!(!inputs.is_empty());
-        let mut result = vec![];
+        let mut result = Vec::with_capacity(inputs.len());
 
         for input in inputs.iter() {
             let mut output = input.to_owned();