Training, scoring and deployment of various models on Microsoft Azure using the Azure Machine Learning Python SDK
By writing scripts to create and manage resources, you can:
- Run machine learning operations from your preferred development environment.
- Automate asset creation and configuration to make it repeatable.
- Ensure consistency for resources that must be replicated in multiple environments (for example, development, test, and production)
- Incorporate machine learning asset configuration into developer operations (DevOps) workflows, such as continuous integration / continuous deployment (CI/CD) pipelines.
This Repo is a collection of Machine Learning Projects executed on the Azure Machine Learning Studio using the Python SDK. This project was also executed from a local machine, using the appropriate configurations.
Connection to the Azure Machine Learning Workspace is obtained using the Subscription Group, Resource Group and Workspace name, which has been created from the Azure Portal.
The results are displayed below in different stages