Introduction
Microsoft Azure Machine Learning Fundamentals: Introduction
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1. Introduction to Machine Learning
Learning objectives
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Understand machine learning
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Explore the machine learning workflow
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Learn how to select the right algorithms
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Discover data-centric machine learning
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Demo: Create an Azure machine learning workspace
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Lab: Create an Azure machine learning workspace
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2. Introduction to Azure Machine Learning
What is Azure machine learning?
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Azure machine learning in context
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Azure machine learning workspaces
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Azure Machine Learning Studio
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Leverage the Azure Machine Learning SDK
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Demo: Exploring the Azure Machine Learning designer
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Lab: Running experiments with SDK
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3. Improve Your Azure Machine Learning Model
Learning objectives
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Hyperparameter tuning
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Automated machine learning
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Introduction to bias/variance trade-off
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Demo: Automated machine learning
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Lab: Tuning hyperparameters
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4. Deploy and Monitor Your Model
Learning objectives
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Deploy and consume your model
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CI/CD with machine learning
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Monitor data drift and use Application Insights
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Demo: Deploy your model and monitor with Application Insights
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Lab: Monitor data drift
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5. Interpret Your Model
Introduction to explainers
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Global and local feature importance
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Detect and mitigate fairness
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Demo: Interpret your model
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Lab: Detect and mitigate unfairness
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Learning objectives
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Summary
Microsoft Azure Machine Learning Fundamentals: Summary
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