- [Instructor] Now that we have our app tied in … to our Azure back end, we can try it out. … So I'm going to try it out in the iOS Simulator. … So we'll change our startup project to MLSampleiOS. … So I'll click on it, right click, … and Set a Startup Project. … And then we're going to press the Run button … to compile and run our application. … So the first thing we're testing is Lewis … to see if it can understand the intent … of what we're trying to do. … I need some help, I don't know what to do. … It'll press send. … All right, so it looks like we can evaluate … the contents of an image, so let's try that out. … And we'll try evaluate … the contents of an image. … And press send. … All right, so it's figured out … that we wanted to do visual recognition. … So it's got a bunch of pictures of trees here, … and let's click on one to figure out … if it can show us what kind of tree this is. … It's waiting here, all right, … and it did detect that that was a palm tree. … Let's do another one. …
- 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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