- [Instructor] Now that we've implemented … our core ML models in the app, … we can run the app and see how it works. … Since this will only work in iOS, … I'm going to click on MLSample … and make sure that's set as our start up project … and press the run button. … Now one thing you'll notice about … our language recognition model that we created … is if we type a single word response, … let's just use something like help. … It's not going to understand what it is. … But if I type in need help, … it will. … So lets try some visual recognition. … And you might want to exercise the app a little bit. … Try it a bunch of different ways … so that you can phrase this … and if you phrase this in ways … that it doesn't understand what you want it to do, … that's an opportunity to retrain your model … before you send it out. … So we're going to hit send here. … It's going into visual recognition … and here we have our pictures of trees. … I'll click here … and it came back with a maple tree, that's correct. …
- 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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