diff --git a/examples/backprop.ml b/examples/backprop.ml
index e838fbbeb..d714918aa 100755
--- a/examples/backprop.ml
+++ b/examples/backprop.ml
@@ -1,9 +1,11 @@
-#!/usr/bin/env owl
 (* This example demonstrates how to write the backpropogation algorithm from
    scratch using Algodiff module. With the backprop algorithm, we further make
    a naive neural network without using Owl' DNN to train on mnist dataset.
+
+   Execute 'Dataset.download_all ()' to accquire all necessary dataset before running this example.'
  *)
 
+
 open Owl
 
 open Algodiff.S
@@ -49,7 +51,7 @@ let backprop nn eta x y =
   loss |> unpack_flt
 
 let test nn x y =
-  Dense.Matrix.S.iter2_rows (fun u v ->
+  Dense.Matrix.S.iter2_rows (fun u _ ->
     Dataset.print_mnist_image u;
     let p = run_network (Arr u) nn |> unpack_arr in
     Dense.Matrix.Generic.print p;
diff --git a/examples/checkpoint.ml b/examples/checkpoint.ml
index 27a72e3bb..5c66bc475 100755
--- a/examples/checkpoint.ml
+++ b/examples/checkpoint.ml
@@ -1,4 +1,3 @@
-#!/usr/bin/env owl
 (* This example shows how to use checkpoint in a stateful optimisation. *)
 
 open Owl
diff --git a/examples/cifar10_vgg.ml b/examples/cifar10_vgg.ml
index 460d40166..13ac3d31f 100755
--- a/examples/cifar10_vgg.ml
+++ b/examples/cifar10_vgg.ml
@@ -1,4 +1,3 @@
-#!/usr/bin/env owl
 (* This example demonstrates how to build a VGG-like convolutional neural
  * network for CIFAR10 dataset.
  *)
diff --git a/examples/computation_graph_01.ml b/examples/computation_graph_01.ml
index 91b82c603..837570d23 100755
--- a/examples/computation_graph_01.ml
+++ b/examples/computation_graph_01.ml
@@ -1,4 +1,8 @@
-#!/usr/bin/env owl
+(*
+ * Please install the graphvis tool before executing this example. 
+ E.g. on Ubuntu system: `sudo apt install graphviz`
+*)
+
 
 open Owl
 module G = Owl_computation_cpu_engine.Make (Owl_algodiff_primal_ops.D)
diff --git a/examples/computation_graph_02.ml b/examples/computation_graph_02.ml
index db51470c8..a7fcdd48e 100755
--- a/examples/computation_graph_02.ml
+++ b/examples/computation_graph_02.ml
@@ -1,4 +1,8 @@
-#!/usr/bin/env owl
+(*
+ * Please install the graphvis tool before executing this example. 
+ E.g. on Ubuntu system: `sudo apt install graphviz`
+*)
+
 
 open Owl
 module G = Owl_computation_cpu_engine.Make (Owl_algodiff_primal_ops.D)
diff --git a/examples/dune b/examples/dune
new file mode 100644
index 000000000..594094b39
--- /dev/null
+++ b/examples/dune
@@ -0,0 +1,3 @@
+(executable
+ (name backprop)
+ (libraries owl))
\ No newline at end of file
diff --git a/examples/regression.ml b/examples/regression.ml
index 17cb6a7af..7cac0ffe9 100755
--- a/examples/regression.ml
+++ b/examples/regression.ml
@@ -53,12 +53,13 @@ let test_poly () =
   let z = Array.init (n + 1) (fun i -> Mat.(pow_scalar x (float_of_int i)))
     |> Mat.concatenate ~axis:1
   in
-  let y' = Mat.(z *@ p) in
+  Mat.(z *@ p)
+  (* let y' = Mat.(z *@ p) in
   let open Owl_plplot in
   let h = Plot.create "plot_regression.png" in
   Plot.(scatter ~h ~spec:[ RGB (100,100,50) ] x y);
   Plot.(scatter ~h ~spec:[ Marker "+" ] x y');
-  Plot.output h
+  Plot.output h *)
 
 
 let _ =