azure-mgmt-machinelearningservices

Create a Python-based application that integrates with Microsoft Azure's Machine Learning Services using the 'azure-mgmt-machinelearningservices' package. Your application should allow users to manage their Azure Machine Learning resources such as workspaces, compute targets, and datasets directly from the command line or a simple GUI interface. The application should follow these steps:

1. Authenticate the user with Azure using their credentials.
2. Provide a list of available operations such as creating, updating, deleting, and listing machine learning workspaces, compute targets, and datasets.
3. Allow users to create a new machine learning workspace, specifying necessary configurations like name, location, storage account key, etc.
4. Enable users to manage compute targets within their workspaces (e.g., creating a new compute target or deleting an existing one).
5. Support uploading and managing datasets for use in machine learning experiments.
6. Implement a feature to monitor the status of ongoing operations and display any errors or warnings.
7. Ensure that the application provides clear and concise feedback throughout the process, guiding users through each step and providing help where needed.

The 'azure-mgmt-machinelearningservices' package will be utilized to interact with Azure's REST API endpoints for managing machine learning services. This includes authenticating requests, handling responses, and translating between Python objects and Azure resource representations. Users should be able to perform all actions without needing to manually construct HTTP requests or parse JSON responses.