- [Instructor] Now that we have created our model … and are happy with it, we can create a web service. … To do this, we're going to click on Setup Web Service … and you can see we have two types: … a predictive web service and a retraining web service. … The predictive web service takes inputs … and predicts the result; the retraining web service … is to feed real world results back into the model. … We want the one for predictions, so we'll click predictive. … And if for some reason that's not enabled for you, … if you run again, it should show up as enabled, … and you should be able to create the web service. … So we can see it modifying our experiment, … and adding a web service and it creates the predictive … experiment, so if you look to the top of the screen, … we now have two tabs, one for the training experiment, … which is what we created, … and one for the predictive experiment. … And this one is for our web service. … With our model already trained, we don't need to have …
- 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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