From the course: Machine Learning in Mobile Applications
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Prepare Android and iOS apps to consume non-SSL endpoints
From the course: Machine Learning in Mobile Applications
Prepare Android and iOS apps to consume non-SSL endpoints
The final Azure service you want to tie into is our custom model. If you remember, we set up the endpoint as plain HTTP. As we did not have a certificate, we will need to modify both the Android and iOS apps to allow this. For Android, we're going to create an XML resource. So we'll go under Platforms and Android, and then under the Resources folder we're going to create a new folder and we'll call it "xml". And this should be all lowercase, just like that. And then we'll create a new file in the folder and it will be called "security_config". And this is an XML file. So we'll put the standard XML header on it: 'xml version = "1.0"'. Now if you already have an XML file, which we do right here with colors, I bet you we can get this right like that. So I'm going to be lazy and this will hopefully stop us from making some possible typos. And then we want to add in a node for network security configuration. And we also want a closing node for that. And we'll add inside that a domain…
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Azure Machine Learning overview3m 12s
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Language Understanding: Setup2m 51s
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Language Understanding: Using Language Studio5m 10s
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Language Understanding: Train, deploy, and test2m 19s
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Custom Vision: Setup5m 33s
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Azure Machine Learning Studio: Setup3m 13s
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Azure Machine Learning Studio: Create a model2m 16s
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Azure Machine Learning Studio: Deploy and test a model4m 8s
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Install the SDK in a mobile app2m 33s
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Tie to Language Understanding7m 21s
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Tie to Custom Vision7m 22s
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Prepare Android and iOS apps to consume non-SSL endpoints6m 34s
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Tie to the Azure Machine Learning Studio model7m
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Running the app2m 32s
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Challenge: Create a custom Language Understanding model2m 39s
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Solution: Create a custom Language Understanding model4m 10s
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