- [Man] We set up our app to call … into a few Watson services. … One for language understanding, … one for image classification, … and one a totally custom model we made. … So, let's try our app out. … So, on the right we have our IOS simulator. … And I'm going to make sure that the IOS project … is selected as our start-up project … and we can right click on it, … and say set a start up. … And then I'm going to hit the run button. … And this is going to compile our app … and push it out to the simulator. … So, here we have a conversational UI. … On the bottom we have a text box we can type into … so let's find out what we can do. … So, we're going to say hi and press send. … Oh, hello and welcome. … So, it obviously understood … what we wanted to do. … So, I'll type in I don't know what to do. … Alright. … It comes back and tells me … what I can actually do. … So, one of the things that we can do … is evaluate the contents of an image. … So, let's go look at the contents of an image. …
Author
Released
3/21/2019- 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
Duration
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Introduction
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What you should know1m 1s
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Using the exercise files2m 36s
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1. Introduction to Machine Learning
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What is machine learning?2m 27s
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Required concepts2m 53s
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Training a model2m 14s
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ML frameworks2m 56s
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2. Server Models: IBM Watson
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Overview of Watson2m 1s
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Visual Recognition: Set up1m 41s
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Create a custom model3m 37s
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Install client SDK package3m 45s
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Run the client app3m 27s
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3. Server Models: Azure Machine Learning
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Custom Vision: Set up4m 25s
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Install client SDK package2m 27s
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Client tie to LUIS5m 16s
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Run the clent app2m 12s
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4. Client Models: Core ML
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Core ML overview2m 10s
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Run the client app1m 45s
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5. Understanding the Offerings
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Conclusion
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Next steps1m 40s
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Video: Run the client app