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Skin cancer detection/readme.md

@@ -29,11 +29,12 @@ To bring the trained model on an iPhone and run it on the phone without any conn
 Now to use this CoreML model witha Xamarin app, we follow 4 steps:
 1) Download a sample Xamarin app from here (https://github.com/Azure-Samples/cognitive-services-ios-customvision-sample)
 2) We replace the Custom Vision API model here with our custom model which we created using AML Workbench.
-3) We compile the coreml model in Xcode 9 or manually using the xcrun command. 
-4) We add a compiled CoreML model to the Resources directory of the project.  
-5) Next I change the name of the model in the controller file and load the compiled model here 
-6) In view controller, we change the result extraction function to output the messages we want the app to spit out. 
-7) Please see the edited AzureML.CoreML.Video folder for the changes we made to the sample app (mentioned in step one)
+3) We follow the instructions in this link (https://developer.xamarin.com/guides/ios/platform_features/introduction-to-ios11/coreml/).
+4) We compile the coreml model in Xcode 9 or manually using the xcrun command. 
+5) We add a compiled CoreML model to the Resources directory of the project.  
+6) Next I change the name of the model in the controller file and load the compiled model here 
+7) In view controller, we change the result extraction function to output the messages we want the app to spit out. 
+8) Please see the edited AzureML.CoreML.Video folder for the changes we made to the sample app (mentioned in step one)
 
 Thus we have a video version of the Xamarin app here which uses a real-time video feed as input and outputs a label. If the predicted label is at risk, the app suggests see a doctor. If the predicted label is not at risk, the app indicates all clear.