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Pre-requisites for Day 1
- Python skills
- Understanding of key concepts of Azure ML
- Get familiar with Azure ML by running other experiments, trying own datasets, extending from previous workshops
- Bring any questions on overall Azure ML, share your feedbacks so far before Day 1
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Day 1 morning
- Intro to agenda, getting to know each other
- Fundamentals
- Creating dev environment: Azure ML Workspace, Compute Instance, Compute Clusters
- What happens when a job is submitted
- Managing experiments and models
- Automated ML: key concept
- Deployment: process recap and init/run structure
- (Optional) Monitoring (swagger and app insights)
- (Optional) Light touch on others (pipeline, designer, data drift, interpretability etc)
- Discussions
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Day 1 afternoon
- Automated ML
- Recap options
- Things covered by Automated ML, things covered by people
- How to check logs & outputs
- ML Pipeline
- Discussions
- Automated ML