diff --git a/examples/tutorial_custom_visualization.py b/examples/tutorial_custom_visualization.py
new file mode 100644
index 0000000..9323e23
--- /dev/null
+++ b/examples/tutorial_custom_visualization.py
@@ -0,0 +1,104 @@
+import numpy as np
+import matplotlib.pylab as plt
+
+from hyppopy.HyppopyProject import HyppopyProject
+from hyppopy.VirtualFunction import VirtualFunction
+from hyppopy.BlackboxFunction import BlackboxFunction
+from hyppopy.solver.HyperoptSolver import HyperoptSolver
+from hyppopy.solver.OptunitySolver import OptunitySolver
+from hyppopy.solver.RandomsearchSolver import RandomsearchSolver
+
+project = HyppopyProject()
+project.add_hyperparameter(name="axis_00", domain="uniform", data=[0, 1], dtype="float")
+project.add_hyperparameter(name="axis_01", domain="uniform", data=[0, 800], dtype="float")
+project.add_hyperparameter(name="axis_02", domain="uniform", data=[-1, 1], dtype="float")
+project.add_hyperparameter(name="axis_03", domain="uniform", data=[0, 5], dtype="float")
+project.add_hyperparameter(name="axis_04", domain="uniform", data=[1, 10000], dtype="float")
+project.add_hyperparameter(name="axis_05", domain="uniform", data=[0, 10], dtype="float")
+project.add_settings(section="solver", name="max_iterations", value=500)
+project.add_settings(section="custom", name="use_solver", value="hyperopt")
+
+plt.ion()
+fig, axes = plt.subplots(nrows=2, ncols=3, figsize=(12, 8))
+plot_data = {"iterations": [],
+             "loss": [],
+             "axis_00": [],
+             "axis_01": [],
+             "axis_02": [],
+             "axis_03": [],
+             "axis_04": [],
+             "axis_05": []}
+
+
+def my_visualization_function(**kwargs):
+    print("\r{}".format(kwargs), end="")
+    plot_data["iterations"].append(kwargs['iterations'])
+    plot_data["loss"].append(kwargs['loss'])
+    plot_data["axis_00"].append(kwargs['axis_00'])
+    plot_data["axis_01"].append(kwargs['axis_01'])
+    plot_data["axis_02"].append(kwargs['axis_02'])
+    plot_data["axis_03"].append(kwargs['axis_03'])
+    plot_data["axis_04"].append(kwargs['axis_04'])
+    plot_data["axis_05"].append(kwargs['axis_05'])
+
+    axes[0, 0].clear()
+    axes[0, 0].plot(plot_data["loss"], plot_data["axis_00"], ".r")
+    axes[0, 0].set_xlabel("loss")
+    axes[0, 0].set_ylabel("axis_00")
+
+    axes[0, 1].clear()
+    axes[0, 1].plot(plot_data["loss"], plot_data["axis_01"], ".r")
+    axes[0, 1].set_xlabel("loss")
+    axes[0, 1].set_ylabel("axis_01")
+
+    axes[0, 2].clear()
+    axes[0, 2].plot(plot_data["loss"], plot_data["axis_02"], ".r")
+    axes[0, 2].set_xlabel("loss")
+    axes[0, 2].set_ylabel("axis_02")
+
+    axes[1, 0].clear()
+    axes[1, 0].plot(plot_data["loss"], plot_data["axis_03"], ".r")
+    axes[1, 0].set_xlabel("loss")
+    axes[1, 0].set_ylabel("axis_03")
+
+    axes[1, 1].clear()
+    axes[1, 1].plot(plot_data["loss"], plot_data["axis_04"], ".r")
+    axes[1, 1].set_xlabel("loss")
+    axes[1, 1].set_ylabel("axis_04")
+
+    axes[1, 2].clear()
+    axes[1, 2].plot(plot_data["loss"], plot_data["axis_05"], ".r")
+    axes[1, 2].set_xlabel("loss")
+    axes[1, 2].set_ylabel("axis_05")
+
+    plt.draw()
+    plt.tight_layout()
+    plt.pause(0.001)
+    
+
+def my_loss_function(data, params):
+    vfunc = VirtualFunction()
+    vfunc.load_default(6)
+    return vfunc(**params)
+
+
+blackbox = BlackboxFunction(data=[],
+                            blackbox_func=my_loss_function,
+                            callback_func=my_visualization_function)
+
+if project.custom_use_solver == "hyperopt":
+    solver = HyperoptSolver(project)
+elif project.custom_use_solver == "optunity":
+    solver = OptunitySolver(project)
+elif project.custom_use_solver == "randomsearch":
+    solver = RandomsearchSolver(project)
+
+if solver is not None:
+    solver.blackbox = blackbox
+solver.run()
+df, best = solver.get_results()
+
+print("\n")
+print("*" * 100)
+print("Best Parameter Set:\n{}".format(best))
+print("*" * 100)
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