diff --git a/.gitignore b/.gitignore
index 01adc20..a412b2a 100644
--- a/.gitignore
+++ b/.gitignore
@@ -56,3 +56,5 @@ Mkfile.old
 dkms.conf
 /.idea/.name
 /.idea/misc.xml
+/.idea/shelf/Uncommitted_changes_before_Update_at_21_09_23,_09_38_[Changes]/shelved.patch
+/.idea/shelf/Uncommitted_changes_before_Update_at_21_09_23,_09_38_[Changes]/shelved.patch
diff --git a/main.c b/main.c
index 0407567..8ddb221 100644
--- a/main.c
+++ b/main.c
@@ -5,25 +5,13 @@
 #include "neuronal_network.h"
 
 int main() {
-//    Image** images = import_images("../data/train-images.idx3-ubyte", "../data/train-labels.idx1-ubyte", NULL, 2);
-//    img_visualize(images[1]);
+//    Image** images = import_images("../data/train-images.idx3-ubyte", "../data/train-labels.idx1-ubyte", NULL, 60000);
+//    img_visualize(images[4]);
 
 //    Neural_Network* nn = new_network(4, 2, 3, 0.5);
-//
-//    int n = 20;
-//
-//    matrix_randomize(nn->bias_1, n);
-//    matrix_randomize(nn->bias_2, n);
-//    matrix_randomize(nn->bias_3, n);
-//
-//    matrix_randomize(nn->weights_1, n);
-//    matrix_randomize(nn->weights_2, n);
-//    matrix_randomize(nn->weights_3, n);
-//
-//    matrix_randomize(nn->weights_output, n);
-//
+//    randomize_network(nn, 20);
 //    save_network(nn);
 
-    Neural_Network* nn = load_network("../networks/test1.txt");
+//    Neural_Network* nn = load_network("../networks/test1.txt");
 
 }
\ No newline at end of file
diff --git a/matrix.c b/matrix.c
index 4cb9ca7..da25e3e 100644
--- a/matrix.c
+++ b/matrix.c
@@ -2,8 +2,10 @@
 #include <stdlib.h>
 #include <stdio.h>
 #include <math.h>
+#include <time.h>
 #define MAX_BYTES 100
 
+static int RANDOMIZED = 0;
 // operational functions
 Matrix* matrix_create(int rows, int columns) {
 
@@ -17,7 +19,7 @@ Matrix* matrix_create(int rows, int columns) {
     // allocate memory for the numbers (2D-Array)
     matrix->numbers = malloc(sizeof(double*) * rows);
     for (int i = 0; i < rows; i++) {
-        matrix->numbers[i] = malloc(sizeof(double) * columns);
+        matrix->numbers[i] = calloc(sizeof(double), columns);
     }
 
     // return the pointer to the allocated memory
@@ -189,7 +191,8 @@ Matrix* apply(double (*function)(double), Matrix* matrix) {
     // apply the function to all values in the matrix
     for (int i = 0; i < matrix->rows; i++) {
         for (int j = 0; j < matrix->columns; j++) {
-            matrix->numbers[i][j] = (*function)(matrix->numbers[i][j]);
+            result_matrix->numbers[i][j] = (*function)(matrix->numbers[i][j]);
+            int k = 0;
         }
     }
 
@@ -246,7 +249,6 @@ Matrix* transpose(Matrix* matrix) {
 
 }
 
-//file operations
 void matrix_save(Matrix* matrix, char* file_string){
 
     // open the file in append mode
@@ -274,30 +276,40 @@ void matrix_save(Matrix* matrix, char* file_string){
 }
 
 Matrix* matrix_load(char* file_string){
+
     FILE *fptr = fopen(file_string, "r");
+
     if(!fptr){
         printf("Could not open \"%s\"", file_string);
         exit(1);
     }
+
+    Matrix * m = load_next_matrix(fptr);
+
+    fclose(fptr);
+    return m;
+}
+
+Matrix* load_next_matrix(FILE *save_file){
+
     char buffer[MAX_BYTES];
 
-    fgets(buffer, MAX_BYTES, fptr);
+    fgets(buffer, MAX_BYTES, save_file);
     int rows = (int)strtol(buffer, NULL, 10);
-    fgets(buffer, MAX_BYTES, fptr);
+    fgets(buffer, MAX_BYTES, save_file);
     int cols = (int)strtol(buffer, NULL, 10);
 
     Matrix *matrix = matrix_create(rows, cols);
 
     for(int i = 0; i < rows; i++){
         for(int j = 0; j < cols; j++){
-            fgets(buffer, MAX_BYTES, fptr);
+            fgets(buffer, MAX_BYTES, save_file);
             matrix->numbers[i][j] = strtod(buffer, NULL);
         }
     }
     return matrix;
 }
 
-
 Matrix* matrix_flatten(Matrix* matrix, int axis) {
     // Axis = 0 -> Column Vector, Axis = 1 -> Row Vector
     Matrix* result_matrix;
@@ -340,6 +352,10 @@ int matrix_argmax(Matrix* matrix) {
 
 void matrix_randomize(Matrix* matrix, int n) {
 
+    if(!RANDOMIZED){
+        srand(time(NULL));
+        RANDOMIZED = 1;
+    }
     //make a min and max
     double min = -1.0f / sqrt(n);
     double max = 1.0f / sqrt(n);
diff --git a/matrix.h b/matrix.h
index 1e88e47..429d5bf 100644
--- a/matrix.h
+++ b/matrix.h
@@ -1,4 +1,5 @@
 #pragma once
+#include <stdio.h>
 
 typedef struct {
     int rows, columns;
@@ -15,6 +16,7 @@ void matrix_print(Matrix *matrix);
 Matrix* matrix_copy(Matrix *matrix);
 void matrix_save(Matrix* matrix, char* file_string);
 Matrix* matrix_load(char* file_string);
+Matrix* load_next_matrix(FILE * save_file);
 
 void matrix_randomize(Matrix* matrix, int n); // don't understand the usage of the n
 int matrix_argmax(Matrix* matrix);
diff --git a/neuronal_network.c b/neuronal_network.c
index 4ff2ac9..e1c6c7f 100644
--- a/neuronal_network.c
+++ b/neuronal_network.c
@@ -115,8 +115,17 @@ Neural_Network* load_network(char* file) {
     // create a new network to fill with the saved data
     Neural_Network* saved_network = new_network(input_size, hidden_size, output_size, 0);
 
+    // load matrices from file into struct
+    saved_network->bias_1 = load_next_matrix(save_file);
+    saved_network->weights_1 = load_next_matrix(save_file);
+    saved_network->bias_2 = load_next_matrix(save_file);
+    saved_network->weights_2 = load_next_matrix(save_file);
+    saved_network->bias_3 = load_next_matrix(save_file);
+    saved_network->weights_3 = load_next_matrix(save_file);
+    saved_network->weights_output = load_next_matrix(save_file);
 
-
+    // return saved network
+    fclose(save_file);
     return saved_network;
 }
 
@@ -162,11 +171,10 @@ Matrix* predict(Neural_Network* network, Matrix* image_data) {
 //void batch_train_network(Neural_Network* network, Image** images, int size);
 
 double relu(double input) {
-    if (input < 0){
+    if (input <= 0){
         return 0.0;
     }
     return input;
-    //TODO: relu formel
 }
 
 Matrix* softmax(Matrix* matrix) {