- [Speaker] To train our visual recognition model … with Watson, we're going to use the curl command … in the Terminal Window. … So we'll start by typing in curl and give it a user … and the user is going to use an API key. … So API key and colon and we can get the API key … in the Watson service we just created. … So I'm going to click on manage, and when this refreshes … we have the API key and I'm going to copy that to … the clipboard and paste that into the terminal window … and we'll close the quotes … and then we will give it some form data and the form data … is going to have our files that we want to upload. … So form and the form data is going to be … our maple tree positive examples … and we're going to say that's equal to, we use the "@", … which is telling it that it's going to grab a file … and we're going to grab that other users … and right off my desktop … and under exercise files … and IBM Watson Collateral … and our maple tree zip … and we'll close the quotes … and I'm going to grab and copy that …
- 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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