remove dolar from loss print

src/evalScript.py

@@ -27,7 +27,7 @@ new_model = tf.keras.models.load_model(modelPath)
 # Evaluate the restored model
 loss = new_model.evaluate(house_price_test_features, house_price_test_expected, verbose=2)
 print("------\n")
-print(f"loss result: ${loss}\n")
+print(f"loss result: {loss}\n")
 print("------")
 
 #print('Restored model, accuracy: {:5.2f}%'.format(100 * acc))
@@ -47,14 +47,14 @@ try:
     y = []
     with open('trainResults.csv', 'r') as trainResults:
         plots = csv.reader(trainResults, delimiter = ',')
-    for row in plots:
-        x.append(row[0])
-        y.append(row[1])
-    plt.bar(x, y, color = 'g', label = "loss")
-    plt.xlabel('builds')
-    plt.ylabel('losses')
-    plt.title('loss for build')
-    plt.legend()
-    plt.show()   
+        for row in plots:
+            x.append(row[0])
+            y.append(row[1])
+        plt.bar(x, y, color = 'g', label = "loss")
+        plt.xlabel('builds')
+        plt.ylabel('losses')
+        plt.title('loss for build')
+        plt.legend()
+        plt.show()   
 except:
     pass