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@@ -7,33 +7,25 @@ The objective of this tutorial is to write a complete image classification progr
 Two classification models will be successively developed and tested: k-nearest neighbors (KNN) and neural networks (NN).
 
 ## Prepare the CIFAR dataset
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 First of all, we had to prepare the CIFAR dataset. All the code can be found on the python file read_cifar.py
 
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 ## K-Nearest Neighbors (KNN)
 
 All the code can be found on the python file knn.py
 
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+Here is the graph of the accuracy of my knn code epending on the value of k for the Cifar dataset with a split factor of 0.9:
+``
 
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+## Artificial Neural Network
 
+### Maths 
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-## Artificial Neural Network
 
+​
 
+### Code