diff --git a/mlpp/hidden_layer/hidden_layer.cpp b/mlpp/hidden_layer/hidden_layer.cpp
index 483c07e..814945b 100644
--- a/mlpp/hidden_layer/hidden_layer.cpp
+++ b/mlpp/hidden_layer/hidden_layer.cpp
@@ -54,8 +54,10 @@ MLPPHiddenLayer::MLPPHiddenLayer(int p_n_hidden, MLPPActivation::ActivationFunct
 	weights->resize(Size2i(input->size().x, n_hidden));
 	bias->resize(n_hidden);
 
-	MLPPUtilities::weight_initializationm(weights, weight_init);
-	MLPPUtilities::bias_initializationv(bias);
+	MLPPUtilities utils;
+
+	utils.weight_initializationm(weights, weight_init);
+	utils.bias_initializationv(bias);
 }
 
 MLPPHiddenLayer::MLPPHiddenLayer() {
diff --git a/mlpp/utilities/utilities.cpp b/mlpp/utilities/utilities.cpp
index 69c116e..a9feca5 100644
--- a/mlpp/utilities/utilities.cpp
+++ b/mlpp/utilities/utilities.cpp
@@ -605,3 +605,23 @@ real_t MLPPUtilities::accuracy(std::vector<real_t> y_hat, std::vector<real_t> y)
 real_t MLPPUtilities::f1_score(std::vector<real_t> y_hat, std::vector<real_t> y) {
 	return 2 * precision(y_hat, y) * recall(y_hat, y) / (precision(y_hat, y) + recall(y_hat, y));
 }
+
+void MLPPUtilities::_bind_methods() {
+	ClassDB::bind_method(D_METHOD("weight_initializationv", "weights", "type"), &MLPPUtilities::weight_initializationv, WEIGHT_DISTRIBUTION_TYPE_DEFAULT);
+	ClassDB::bind_method(D_METHOD("weight_initializationm", "weights", "type"), &MLPPUtilities::weight_initializationm, WEIGHT_DISTRIBUTION_TYPE_DEFAULT);
+	ClassDB::bind_method(D_METHOD("bias_initializationr"), &MLPPUtilities::bias_initializationr);
+	ClassDB::bind_method(D_METHOD("bias_initializationv", "z"), &MLPPUtilities::bias_initializationv);
+
+	ClassDB::bind_method(D_METHOD("performance_vec", "y_hat", "output_set"), &MLPPUtilities::performance_vec);
+	ClassDB::bind_method(D_METHOD("performance_mat", "y_hat", "y"), &MLPPUtilities::performance_mat);
+	ClassDB::bind_method(D_METHOD("performance_pool_int_array_vec", "y_hat", "output_set"), &MLPPUtilities::performance_pool_int_array_vec);
+
+	BIND_ENUM_CONSTANT(WEIGHT_DISTRIBUTION_TYPE_DEFAULT);
+	BIND_ENUM_CONSTANT(WEIGHT_DISTRIBUTION_TYPE_XAVIER_NORMAL);
+	BIND_ENUM_CONSTANT(WEIGHT_DISTRIBUTION_TYPE_XAVIER_UNIFORM);
+	BIND_ENUM_CONSTANT(WEIGHT_DISTRIBUTION_TYPE_HE_NORMAL);
+	BIND_ENUM_CONSTANT(WEIGHT_DISTRIBUTION_TYPE_HE_UNIFORM);
+	BIND_ENUM_CONSTANT(WEIGHT_DISTRIBUTION_TYPE_LE_CUN_NORMAL);
+	BIND_ENUM_CONSTANT(WEIGHT_DISTRIBUTION_TYPE_LE_CUN_UNIFORM);
+	BIND_ENUM_CONSTANT(WEIGHT_DISTRIBUTION_TYPE_UNIFORM);
+}
diff --git a/mlpp/utilities/utilities.h b/mlpp/utilities/utilities.h
index a660744..60685e3 100644
--- a/mlpp/utilities/utilities.h
+++ b/mlpp/utilities/utilities.h
@@ -13,6 +13,8 @@
 #include "core/string/ustring.h"
 #include "core/variant/variant.h"
 
+#include "core/object/reference.h"
+
 #include "../lin_alg/mlpp_matrix.h"
 #include "../lin_alg/mlpp_vector.h"
 
@@ -20,7 +22,9 @@
 #include <tuple>
 #include <vector>
 
-class MLPPUtilities {
+class MLPPUtilities : public Reference {
+	GDCLASS(MLPPUtilities, Reference);
+
 public:
 	// Weight Init
 	static std::vector<real_t> weightInitialization(int n, std::string type = "Default");
@@ -40,10 +44,10 @@ public:
 		WEIGHT_DISTRIBUTION_TYPE_UNIFORM,
 	};
 
-	static void weight_initializationv(Ref<MLPPVector> weights, WeightDistributionType type = WEIGHT_DISTRIBUTION_TYPE_DEFAULT);
-	static void weight_initializationm(Ref<MLPPMatrix> weights, WeightDistributionType type = WEIGHT_DISTRIBUTION_TYPE_DEFAULT);
-	static real_t bias_initializationr();
-	static void bias_initializationv(Ref<MLPPVector> z);
+	void weight_initializationv(Ref<MLPPVector> weights, WeightDistributionType type = WEIGHT_DISTRIBUTION_TYPE_DEFAULT);
+	void weight_initializationm(Ref<MLPPMatrix> weights, WeightDistributionType type = WEIGHT_DISTRIBUTION_TYPE_DEFAULT);
+	real_t bias_initializationr();
+	void bias_initializationv(Ref<MLPPVector> z);
 
 	// Cost/Performance related Functions
 	real_t performance(std::vector<real_t> y_hat, std::vector<real_t> y);
@@ -76,7 +80,10 @@ public:
 	real_t accuracy(std::vector<real_t> y_hat, std::vector<real_t> y);
 	real_t f1_score(std::vector<real_t> y_hat, std::vector<real_t> y);
 
-private:
+protected:
+	static void _bind_methods();
 };
 
+VARIANT_ENUM_CAST(MLPPUtilities::WeightDistributionType);
+
 #endif /* Utilities_hpp */
diff --git a/register_types.cpp b/register_types.cpp
index 19f9db5..227ceaf 100644
--- a/register_types.cpp
+++ b/register_types.cpp
@@ -28,6 +28,7 @@ SOFTWARE.
 #include "mlpp/lin_alg/mlpp_vector.h"
 
 #include "mlpp/regularization/reg.h"
+#include "mlpp/utilities/utilities.h"
 
 #include "mlpp/activation/activation.h"
 
@@ -41,6 +42,7 @@ void register_pmlpp_types(ModuleRegistrationLevel p_level) {
 		ClassDB::register_class<MLPPVector>();
 		ClassDB::register_class<MLPPMatrix>();
 
+		ClassDB::register_class<MLPPUtilities>();
 		ClassDB::register_class<MLPPReg>();
 
 		ClassDB::register_class<MLPPActivation>();