Update README.md

Author: anilsathyan7

README.md

@@ -58,6 +58,37 @@ Sample classification results
 
 ![Screenshot](results/output.png)
 
+### Evaluation
+
+Accuracy of the network on the 550 test images: 99.09%
+Confusion Matrix
+----------------
+[[50  0  0  0  0  0  0  0  0  0  0]
+ [ 0 50  0  0  0  0  0  0  0  0  0]
+ [ 0  0 50  0  0  0  0  0  0  0  0]
+ [ 0  0  0 50  0  0  0  0  0  0  0]
+ [ 0  0  0  0 50  0  0  0  0  0  0]
+ [ 0  4  0  0  0 46  0  0  0  0  0]
+ [ 0  1  0  0  0  0 49  0  0  0  0]
+ [ 0  0  0  0  0  0  0 50  0  0  0]
+ [ 0  0  0  0  0  0  0  0 50  0  0]
+ [ 0  0  0  0  0  0  0  0  0 50  0]
+ [ 0  0  0  0  0  0  0  0  0  0 50]] 
+
+Per class accuracy
+------------------
+Accuracy of class    apple : 100.00 %
+Accuracy of class atm card : 100.00 %
+Accuracy of class   camera : 100.00 %
+Accuracy of class      cat : 100.00 %
+Accuracy of class   banana : 100.00 %
+Accuracy of class   bangle : 92.00 %
+Accuracy of class  battery : 98.00 %
+Accuracy of class   bottle : 100.00 %
+Accuracy of class    broom : 100.00 %
+Accuracy of class     bulb : 100.00 %
+Accuracy of class calender : 100.00 %
+
 ### Observations
 
 1. In **transfer learning**, if your custom dataset is **similar** to the pretrained model's training dataset, then you can easily acheive very **high accuracy**(>90) with very **few training epochs**(<10).