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Demo: Models and Data Resources

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We explore Azure ML Studio's model management features including registering trained models, deploying endpoints with APIs, configuring Python environments for training, and connecting to various data stores like blob storage, SQL databases, and PostgreSQL.

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Previous Module The Azure ML Designer
This Module Running Experiments and Training Models
Introduction to Experiments
Introduction to Experiments
Running Experiments
Running Experiments
Training a Model in a Script
Training a Model in a Script
Using Script Arguments
Using Script Arguments
Registering a Model
Registering a Model
Demo: Models and Data Resources
Demo: Models and Data Resources
Next Module Working With Data