- [Instructor] Now we're ready to call the web service. … So we'll do var response, and that's going to be … equal to await 'cause that's an asynchronous call, … the client and we'll call PostASync. … We're going to pass in our URL and the request content. … And if we get a success status code back, … we'll continue on, … otherwise we're just going to hop out of this method. … And if it is successful, … we need to pull up the response strength, … so we're going to create a variable called contentString. … That's going to be equal to … await_response dot content … ReadAStringAsync. … And that will pull out a JSON object, … or at least a string that represents a JSON object. … Now we could create classes … and de-serialize a string that way, … but we can also do this inline using anonymous object. … This is a very complex JSON object … with several internal arrays, but it's just simple enough … where we should be able to do it inline. … So I'll go var definition equals new, … and this is going to be a JSON object …
- Defining machine learning
- Training a machine learning model
- Comparing machine learning frameworks
- Using IBM Watson for mobile machine learning
- Using Azure Machine Learning for speech and image recognition
- Training Core ML models
- Comparing client-side and server-side models
Skill Level Beginner
Xamarin and Android Studio: Material Designwith Kevin Ford1h 47m Intermediate
Machine Learning for iOS Developerswith Brian Advent1h 25m Advanced
1. Introduction to Machine Learning
2. Server Models: IBM Watson
3. Server Models: Azure Machine Learning
4. Client Models: Core ML
5. Understanding the Offerings
Next steps1m 40s
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