- We are now going to use the Core ML models … we created in Xcode. … As before, we're going to go up to Exercise Files, … click on Client Project Start, … right cligk, and copy Client Project Start, … close the window and we'll paste that to the desktop. … And we're going to rename that folder to Core ML project. … And we can open the folder up, … and we'll double click on ML sample solution … to open this up in Visual Studio. … Earlier, we created models for doing language recognition … and image recognition with core ML. … And we're going to copy those files to our iOS project. … So right here is our iOS project, … so I'm going to take this and drag it, … and drop it right over the ML sample iOS. … And we're going to copy the file to the directory and press OK, … and we're going to do the same with our image classifier. … Drop it on, copy and say OK. … We do want to go to each one of these … and right click on it, and look at its properties … and make sure that the build action … is Core ML Model, which it is here. …
- 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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