Introduction
Machine learning in mobile apps
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What you should know
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Using the exercise files
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1. Introduction to Machine Learning
What is machine learning?
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Required concepts
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Why does this matter for my app?
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Training a model
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Machine learning vs. deep learning
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What can I do with machine learning?
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Server-side vs. client-side ML
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ML frameworks
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2. Server Models: IBM Watson
Overview of Watson
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Natural Language Understanding: Set up
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Natural Language Understanding: Train the model
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Visual Recognition: Set up
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Visual Recognition: Train the model
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Create a custom model
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Train and deploy a custom model
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Install client SDK package
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Client tie to Natural Language
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Client tie to Visual Recognition call setup
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Client tie to Visual Recognition response
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Client tie to custom model: Get an access token
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Client tie to call custom model service
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Client tie to get custom model response
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Run the client app
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3. Server Models: Azure Machine Learning
Azure Machine Learning overview
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Language Understanding: Set up
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Language Understanding: Intents
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Language Understanding: Utterances
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Custom Vision: Set up
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Machine Learning Studio: Set up
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Machine Learning Studio: Create model
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Machine Learning Studio: Publish model
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Install client SDK package
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Client tie to LUIS
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Client tie to Custom Vision model
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Client tie to custom model
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Client tie to custom model: Set up request
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Client tie to custom model: Make the call
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Run the clent app
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4. Client Models: Core ML
Core ML overview
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Core ML: Create Natural Language model
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Core ML: Create Visual Recognition model
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Client tie to Natural Language model
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Client tie to Visual Recognition model
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Client tie to Visual Recognition: Converting model
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Run the client app
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5. Understanding the Offerings
Different philosopies of the vendors
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Why client-side model vs. server-side
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When to use one or the other of these solutions
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Ex_Files_Machine_Learning_Mobile_App.zip
(198.0 MB)